diff --git a/README.md b/README.md
index 91b77bc91d7e76c543320f1a2517ee696ae93607..6661d4e9d9b0e47eff88b4fdb332e00191322f55 100755
--- a/README.md
+++ b/README.md
@@ -29,6 +29,7 @@ Pro svou práci si naklonujete Gitem repozitář do svĂ©ho pracovnĂho adresář
|0.47|11m7s|přidánà filtrů pro opravu a nahrazenà tabulek, vylepšenà filtrace, ...|
|0.51|16m37s|export do pdf, export do epub, filtry, ...|
|0.52|16m37s|oprava exportu do pdf, nový filtr pro poslednà opravu formátovánà a chyb, ...|
+|0.53|17m37s|oprava exportu do pdf a epub|
>**Problémy**
> * internĂ a externĂ odkazy
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diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/accessing-the-cluster/outgoing-connections.md b/converted/docs.it4i.cz/anselm-cluster-documentation/accessing-the-cluster/outgoing-connections.md
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@@ -0,0 +1,118 @@
+Outgoing connections
+====================
+
+
+
+Connection restrictions
+-----------------------
+
+Outgoing connections, from Anselm Cluster login nodes to the outside
+world, are restricted to following ports:
+
+ |Port|Protocol|
+ |---|---|
+ |22|ssh|
+ |80|http|
+ |443|https|
+ |9418|git|
+
+Please use **ssh port forwarding** and proxy servers to connect from
+Anselm to all other remote ports.
+
+Outgoing connections, from Anselm Cluster compute nodes are restricted
+to the internal network. Direct connections form compute nodes to
+outside world are cut.
+
+Port forwarding
+---------------
+
+### Port forwarding from login nodes
+
+Port forwarding allows an application running on Anselm to connect to
+arbitrary remote host and port.
+
+It works by tunneling the connection from Anselm back to users
+workstation and forwarding from the workstation to the remote host.
+
+Pick some unused port on Anselm login node (for example 6000) and
+establish the port forwarding:
+
+`
+local $ ssh -R 6000:remote.host.com:1234 anselm.it4i.cz
+`
+
+In this example, we establish port forwarding between port 6000 on
+Anselm and port 1234 on the remote.host.com. By accessing
+localhost:6000 on Anselm, an application will see response of
+remote.host.com:1234. The traffic will run via users local workstation.
+
+Port forwarding may be done **using PuTTY** as well. On the PuTTY
+Configuration screen, load your Anselm configuration first. Then go to
+Connection->SSH->Tunnels to set up the port forwarding. Click
+Remote radio button. Insert 6000 to Source port textbox. Insert
+remote.host.com:1234. Click Add button, then Open.
+
+Port forwarding may be established directly to the remote host. However,
+this requires that user has ssh access to remote.host.com
+
+`
+$ ssh -L 6000:localhost:1234 remote.host.com
+`
+
+Note: Port number 6000 is chosen as an example only. Pick any free port.
+
+### Port forwarding from compute nodes
+
+Remote port forwarding from compute nodes allows applications running on
+the compute nodes to access hosts outside Anselm Cluster.
+
+First, establish the remote port forwarding form the login node, as
+[described
+above](outgoing-connections.html#port-forwarding-from-login-nodes).
+
+Second, invoke port forwarding from the compute node to the login node.
+Insert following line into your jobscript or interactive shell
+
+`
+$ ssh -TN -f -L 6000:localhost:6000 login1
+`
+
+In this example, we assume that port forwarding from login1:6000 to
+remote.host.com:1234 has been established beforehand. By accessing
+localhost:6000, an application running on a compute node will see
+response of remote.host.com:1234
+
+### Using proxy servers
+
+Port forwarding is static, each single port is mapped to a particular
+port on remote host. Connection to other remote host, requires new
+forward.
+
+Applications with inbuilt proxy support, experience unlimited access to
+remote hosts, via single proxy server.
+
+To establish local proxy server on your workstation, install and run
+SOCKS proxy server software. On Linux, sshd demon provides the
+functionality. To establish SOCKS proxy server listening on port 1080
+run:
+
+`
+local $ ssh -D 1080 localhost
+`
+
+On Windows, install and run the free, open source [Sock
+Puppet](http://sockspuppet.com/) server.
+
+Once the proxy server is running, establish ssh port forwarding from
+Anselm to the proxy server, port 1080, exactly as [described
+above](outgoing-connections.html#port-forwarding-from-login-nodes).
+
+`
+local $ ssh -R 6000:localhost:1080 anselm.it4i.cz
+`
+
+Now, configure the applications proxy settings to **localhost:6000**.
+Use port forwarding to access the [proxy server from compute
+nodes](outgoing-connections.html#port-forwarding-from-compute-nodes)
+as well .
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/accessing-the-cluster/shell-and-data-access/shell-and-data-access.md b/converted/docs.it4i.cz/anselm-cluster-documentation/accessing-the-cluster/shell-and-data-access/shell-and-data-access.md
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@@ -0,0 +1,137 @@
+Shell access and data transfer
+==============================
+
+
+
+Interactive Login
+-----------------
+
+The Anselm cluster is accessed by SSH protocol via login nodes login1
+and login2 at address anselm.it4i.cz. The login nodes may be addressed
+specifically, by prepending the login node name to the address.
+
+ Login address |Port|Protocol| Login node
+ ----------------------- |---|---| ----------------------------------------------
+ anselm.it4i.cz |22|ssh| round-robin DNS record for login1 and login2
+ login1.anselm.it4i.cz |22|ssh| login1
+ login2.anselm.it4i.cz |22|ssh| login2
+
+The authentication is by the [private
+key](../../../get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/ssh-keys.html)
+
+Please verify SSH fingerprints during the first logon. They are
+identical on all login nodes:
+29:b3:f4:64:b0:73:f5:6f:a7:85:0f:e0:0d:be:76:bf (DSA)
+d4:6f:5c:18:f4:3f:70:ef:bc:fc:cc:2b:fd:13:36:b7Â (RSA)
+
+Â
+
+Private key (`id_rsa/id_rsa.ppk` ): `600 (-rw-------)`s authentication:
+
+On **Linux** or **Mac**, use
+
+`
+local $ ssh -i /path/to/id_rsa username@anselm.it4i.cz
+`
+
+If you see warning message "UNPROTECTED PRIVATE KEY FILE!", use this
+command to set lower permissions to private key file.
+
+`
+local $ chmod 600 /path/to/id_rsa
+`
+
+On **Windows**, use [PuTTY ssh
+client](../../../get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/putty/putty.html).
+
+After logging in, you will see the command prompt:
+
+ _
+ / | |
+ / _ __ ___ ___| |_ __ ___
+ / / | '_ / __|/ _ | '_ ` _
+ / ____ | | | __ __/ | | | | | |
+ /_/ __| |_|___/___|_|_| |_| |_|
+
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â http://www.it4i.cz/?lang=en
+
+ Last login: Tue Jul 9 15:57:38 2013 from your-host.example.com
+ [username@login2.anselm ~]$
+
+The environment is **not** shared between login nodes, except for
+[shared filesystems](../storage-1.html#section-1).
+
+Data Transfer
+-------------
+
+Data in and out of the system may be transferred by the
+[scp](http://en.wikipedia.org/wiki/Secure_copy) and sftp
+protocols. (Not available yet.) In case large
+volumes of data are transferred, use dedicated data mover node
+dm1.anselm.it4i.cz for increased performance.
+
+ |Address|Port|Protocol|
+ -------------------- |---|---|- -----------------------------------------
+ |anselm.it4i.cz|22|scp, sftp|
+ |login1.anselm.it4i.cz|22|scp, sftp|
+ |login2.anselm.it4i.cz|22|scp, sftp|
+ |dm1.anselm.it4i.cz|22|scp, sftp|
+
+Â The authentication is by the [private
+key](../../../get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/ssh-keys.html)
+
+Data transfer rates up to **160MB/s** can be achieved with scp or sftp.
+ may be transferred in 1:50h.
+
+To achieve 160MB/s transfer rates, the end user must be connected by 10G
+line all the way to IT4Innovations and use computer with fast processor
+for the transfer. Using Gigabit ethernet connection, up to 110MB/s may
+be expected. Fast cipher (aes128-ctr) should be used.
+
+If you experience degraded data transfer performance, consult your local
+network provider.
+
+On linux or Mac, use scp or sftp client to transfer the data to Anselm:
+
+`
+local $ scp -i /path/to/id_rsa my-local-file username@anselm.it4i.cz:directory/file
+`
+
+`
+local $ scp -i /path/to/id_rsa -r my-local-dir username@anselm.it4i.cz:directory
+`
+
+ or
+
+`
+local $ sftp -o IdentityFile=/path/to/id_rsa username@anselm.it4i.cz
+`
+
+Very convenient way to transfer files in and out of the Anselm computer
+is via the fuse filesystem
+[sshfs](http://linux.die.net/man/1/sshfs)
+
+`
+local $ sshfs -o IdentityFile=/path/to/id_rsa username@anselm.it4i.cz:. mountpoint
+`
+
+Using sshfs, the users Anselm home directory will be mounted on your
+local computer, just like an external disk.
+
+Learn more on ssh, scp and sshfs by reading the manpages
+
+`
+$ man ssh
+$ man scp
+$ man sshfs
+`
+
+On Windows, use [WinSCP
+client](http://winscp.net/eng/download.php) to transfer
+the data. The [win-sshfs
+client](http://code.google.com/p/win-sshfs/) provides a
+way to mount the Anselm filesystems directly as an external disc.
+
+More information about the shared file systems is available
+[here](../../storage.html).
+
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diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/accessing-the-cluster/vpn-access.md b/converted/docs.it4i.cz/anselm-cluster-documentation/accessing-the-cluster/vpn-access.md
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@@ -0,0 +1,110 @@
+VPN Access
+==========
+
+
+
+Accessing IT4Innovations internal resources via VPN
+---------------------------------------------------
+
+**Failed to initialize connection subsystem Win 8.1 - 02-10-15 MS
+patch**
+Workaround can be found at
+[https://docs.it4i.cz/vpn-connection-fail-in-win-8.1](../../vpn-connection-fail-in-win-8.1.html)
+
+Â
+
+For using resources and licenses which are located at IT4Innovations
+local network, it is necessary to VPN connect to this network.
+We use Cisco AnyConnect Secure Mobility Client, which is supported on
+the following operating systems:
+
+- >Windows XP
+- >Windows Vista
+- >Windows 7
+- >Windows 8
+- >Linux
+- >MacOS
+
+It is impossible to connect to VPN from other operating systems.
+
+VPN client installation
+------------------------------------
+
+You can install VPN client from web interface after successful login
+with LDAP credentials on address <https://vpn1.it4i.cz/anselm>
+
+
+
+According to the Java settings after login, the client either
+automatically installs, or downloads installation file for your
+operating system. It is necessary to allow start of installation tool
+for automatic installation.
+
+
+
+access](../executionaccess.jpg/@@images/4d6e7cb7-9aa7-419c-9583-6dfd92b2c015.jpeg "Execution access")
+access
+
+
+After successful installation, VPN connection will be established and
+you can use available resources from IT4I network.
+
+
+
+If your Java setting doesn't allow automatic installation, you can
+download installation file and install VPN client manually.
+
+
+
+After you click on the link, download of installation file will start.
+
+
+
+After successful download of installation file, you have to execute this
+tool with administrator's rights and install VPN client manually.
+
+Working with VPN client
+-----------------------
+
+You can use graphical user interface or command line interface to run
+VPN client on all supported operating systems. We suggest using GUI.
+
+Before the first login to VPN, you have to fill
+URLÂ **https://vpn1.it4i.cz/anselm** into the text field.
+
+
+
+After you click on the Connect button, you must fill your login
+credentials.
+
+
+
+After a successful login, the client will minimize to the system tray.
+If everything works, you can see a lock in the Cisco tray icon.
+
+
+
+If you right-click on this icon, you will see a context menu in which
+you can control the VPN connection.
+
+
+
+When you connect to the VPN for the first time, the client downloads the
+profile and creates a new item "ANSELM" in the connection list. For
+subsequent connections, it is not necessary to re-enter the URL address,
+but just select the corresponding item.
+
+
+
+Then AnyConnect automatically proceeds like in the case of first logon.
+
+
+
+After a successful logon, you can see a green circle with a tick mark on
+the lock icon.
+
+
+
+For disconnecting, right-click on the AnyConnect client icon in the
+system tray and select **VPN Disconnect**.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/bullxB510.png b/converted/docs.it4i.cz/anselm-cluster-documentation/bullxB510.png
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@@ -0,0 +1,306 @@
+Compute Nodes
+=============
+
+
+
+Nodes Configuration
+-------------------
+
+Anselm is cluster of x86-64 Intel based nodes built on Bull Extreme
+Computing bullx technology. The cluster contains four types of compute
+nodes.
+
+###Compute Nodes Without Accelerator
+
+-
+
+ 180 nodes
+
+
+
+-
+
+ 2880 cores in total
+
+
+
+-
+
+ two Intel Sandy Bridge E5-2665, 8-core, 2.4GHz processors per node
+
+
+
+-
+
+ 64 GB of physical memory per node
+
+
+
+- one 500GB SATA 2,5” 7,2 krpm HDD per node
+-
+
+ bullx B510 blade servers
+
+
+
+-
+
+ cn[1-180]
+
+
+
+###Compute Nodes With GPU Accelerator
+
+-
+
+ 23 nodes
+
+
+
+-
+
+ 368 cores in total
+
+
+
+-
+
+ two Intel Sandy Bridge E5-2470, 8-core, 2.3GHz processors per node
+
+
+
+-
+
+ 96 GB of physical memory per node
+
+
+
+- one 500GB SATA 2,5” 7,2 krpm HDD per node
+-
+
+ GPU accelerator 1x NVIDIA Tesla Kepler K20 per node
+
+
+
+-
+
+ bullx B515 blade servers
+
+
+
+-
+
+ cn[181-203]
+
+
+
+###Compute Nodes With MIC Accelerator
+
+-
+
+ 4 nodes
+
+
+
+-
+
+ 64 cores in total
+
+
+
+-
+
+ two Intel Sandy Bridge E5-2470, 8-core, 2.3GHz processors per node
+
+
+
+-
+
+ 96 GB of physical memory per node
+
+
+
+- one 500GB SATA 2,5” 7,2 krpm HDD per node
+-
+
+ MIC accelerator 1x Intel Phi 5110P per node
+
+
+
+-
+
+ bullx B515 blade servers
+
+
+
+-
+
+ cn[204-207]
+
+
+
+###Fat Compute Nodes
+
+-
+
+ 2 nodes
+
+
+
+-
+
+ 32 cores in total
+
+
+
+-
+
+ 2 Intel Sandy Bridge E5-2665, 8-core, 2.4GHz processors per node
+
+
+
+-
+
+ 512 GB of physical memory per node
+
+
+
+- two 300GB SAS 3,5”15krpm HDD (RAID1) per node
+-
+
+ two 100GB SLC SSD per node
+
+
+
+-
+
+ bullx R423-E3 servers
+
+
+
+-
+
+ cn[208-209]
+
+
+
+Â
+
+
+
+**Figure Anselm bullx B510 servers**
+
+### Compute Nodes Summary
+
+ |Node type|Count|Range|Memory|Cores|[Access](resource-allocation-and-job-execution/resources-allocation-policy.html)|
+ |---|---|---|---|---|---|
+ |Nodes without accelerator|180|cn[1-180]|64GB|16 @ 2.4Ghz|qexp, qprod, qlong, qfree|
+ |Nodes with GPU accelerator|23|cn[181-203]|96GB|16 @ 2.3Ghz|qgpu, qprod|
+ |Nodes with MIC accelerator|4|cn[204-207]|96GB|16 @ 2.3GHz|qmic, qprod|
+ |Fat compute nodes|2|cn[208-209]|512GB|16 @ 2.4GHz|qfat, qprod|
+
+Processor Architecture
+----------------------
+
+Anselm is equipped with Intel Sandy Bridge processors Intel Xeon E5-2665
+(nodes without accelerator and fat nodes) and Intel Xeon E5-2470 (nodes
+with accelerator). Processors support Advanced Vector Extensions (AVX)
+256-bit instruction set.
+
+### Intel Sandy Bridge E5-2665 Processor
+
+- eight-core
+- speed: 2.4 GHz, up to 3.1 GHz using Turbo Boost Technology
+- peak performance: 19.2 Gflop/s per
+ core
+- caches:
+
+
+ - L2: 256 KB per core
+ - L3: 20 MB per processor
+
+
+
+- memory bandwidth at the level of the processor: 51.2 GB/s
+
+### Intel Sandy Bridge E5-2470 Processor
+
+- eight-core
+- speed: 2.3 GHz, up to 3.1 GHz using Turbo Boost Technology
+- peak performance: 18.4 Gflop/s per
+ core
+- caches:
+
+
+ - L2: 256 KB per core
+ - L3: 20 MB per processor
+
+
+
+- memory bandwidth at the level of the processor: 38.4 GB/s
+
+Â
+
+Nodes equipped with Intel Xeon E5-2665 CPU have set PBS resource
+attribute cpu_freq = 24, nodes equipped with Intel Xeon E5-2470 CPU
+have set PBS resource attribute cpu_freq = 23.
+
+`
+$ qsub -A OPEN-0-0 -q qprod -l select=4:ncpus=16:cpu_freq=24 -I
+`
+
+In this example, we allocate 4 nodes, 16 cores at 2.4GHhz per node.
+
+Intel Turbo Boost Technology is used by default, you can disable it for
+all nodes of job by using resource attribute cpu_turbo_boost.
+
+ $ qsub -A OPEN-0-0 -q qprod -l select=4:ncpus=16 -l cpu_turbo_boost=0 -I
+
+Memory Architecture
+-------------------
+
+### Compute Node Without Accelerator
+
+- 2 sockets
+- Memory Controllers are integrated into processors.
+
+
+ - 8 DDR3 DIMMS per node
+ - 4 DDR3 DIMMS per CPU
+ - 1 DDR3 DIMMS per channel
+ - Data rate support: up to 1600MT/s
+
+
+
+- Populated memory: 8x 8GB DDR3 DIMM 1600Mhz
+
+### Compute Node With GPU or MIC Accelerator
+
+- 2 sockets
+- Memory Controllers are integrated into processors.
+
+
+ - 6 DDR3 DIMMS per node
+ - 3 DDR3 DIMMS per CPU
+ - 1 DDR3 DIMMS per channel
+ - Data rate support: up to 1600MT/s
+
+
+
+- Populated memory: 6x 16GB DDR3 DIMM 1600Mhz
+
+### Fat Compute Node
+
+- 2 sockets
+- Memory Controllers are integrated into processors.
+
+
+ - 16 DDR3 DIMMS per node
+ - 8 DDR3 DIMMS per CPU
+ - 2 DDR3 DIMMS per channel
+ - Data rate support: up to 1600MT/s
+
+
+
+- Populated memory: 16x 32GB DDR3 DIMM 1600Mhz
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/environment-and-modules.md b/converted/docs.it4i.cz/anselm-cluster-documentation/environment-and-modules.md
new file mode 100644
index 0000000000000000000000000000000000000000..80ac34c467c727502fa3aff1eadafcf0098ee80b
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/environment-and-modules.md
@@ -0,0 +1,114 @@
+Environment and Modules
+=======================
+
+
+
+### Environment Customization
+
+After logging in, you may want to configure the environment. Write your
+preferred path definitions, aliases, functions and module loads in the
+.bashrc file
+
+`
+# ./bashrc
+
+# Source global definitions
+if [ -f /etc/bashrc ]; then
+ . /etc/bashrc
+fi
+
+# User specific aliases and functions
+alias qs='qstat -a'
+module load PrgEnv-gnu
+
+# Display informations to standard output - only in interactive ssh session
+if [ -n "$SSH_TTY" ]
+then
+ module list # Display loaded modules
+fi
+`
+
+Do not run commands outputing to standard output (echo, module list,
+etc) in .bashrc for non-interactive SSH sessions. It breaks fundamental
+functionality (scp, PBS) of your account! Take care for SSH session
+interactivity for such commands as
+ stated in the previous example.
+in the previous example.
+
+### Application Modules
+
+In order to configure your shell for running particular application on
+Anselm we use Module package interface.
+
+The modules set up the application paths, library paths and environment
+variables for running particular application.
+
+We have also second modules repository. This modules repository is
+created using tool called EasyBuild. On Salomon cluster, all modules
+will be build by this tool. If you want to use software from this
+modules repository, please follow instructions in section [Application
+Modules
+Path Expansion](environment-and-modules.html#EasyBuild).
+
+The modules may be loaded, unloaded and switched, according to momentary
+needs.
+
+To check available modules use
+
+`
+$ module avail
+`
+
+To load a module, for example the octave module use
+
+`
+$ module load octave
+`
+
+loading the octave module will set up paths and environment variables of
+your active shell such that you are ready to run the octave software
+
+To check loaded modules use
+
+`
+$ module list
+`
+
+Â To unload a module, for example the octave module use
+
+`
+$ module unload octave
+`
+
+Learn more on modules by reading the module man page
+
+`
+$ man module
+`
+
+Following modules set up the development environment
+
+PrgEnv-gnu sets up the GNU development environment in conjunction with
+the bullx MPI library
+
+PrgEnv-intel sets up the INTEL development environment in conjunction
+with the Intel MPI library
+
+### Application Modules Path Expansion
+
+All application modules on Salomon cluster (and further) will be build
+using tool called
+[EasyBuild](http://hpcugent.github.io/easybuild/ "EasyBuild").
+In case that you want to use some applications that are build by
+EasyBuild already, you have to modify your MODULEPATH environment
+variable.
+
+`
+export MODULEPATH=$MODULEPATH:/apps/easybuild/modules/all/
+`
+
+This command expands your searched paths to modules. You can also add
+this command to the .bashrc file to expand paths permanently. After this
+command, you can use same commands to list/add/remove modules as is
+described above.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/hardware-overview.md b/converted/docs.it4i.cz/anselm-cluster-documentation/hardware-overview.md
new file mode 100644
index 0000000000000000000000000000000000000000..e70624ac373dd777964cb9144416af656f6bd55a
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/hardware-overview.md
@@ -0,0 +1,365 @@
+Hardware Overview
+=================
+
+
+
+The Anselm cluster consists of 209 computational nodes named cn[1-209]
+of which 180 are regular compute nodes, 23 GPU Kepler K20 accelerated
+nodes, 4 MIC Xeon Phi 5110 accelerated nodes and 2 fat nodes. Each node
+is a powerful x86-64 computer,
+equipped with 16 cores (two eight-core Intel Sandy Bridge processors),
+at least 64GB RAM, and local hard drive. The user access to the Anselm
+cluster is provided by two login nodes login[1,2]. The nodes are
+interlinked by high speed InfiniBand and Ethernet networks. All nodes
+share 320TB /home disk storage to store the user files. The 146TB shared
+/scratch storage is available for the scratch data.
+
+The Fat nodes are equipped with large amount (512GB) of memory.
+Virtualization infrastructure provides resources to run long term
+servers and services in virtual mode. Fat nodes and virtual servers may
+access 45 TB of dedicated block storage. Accelerated nodes, fat nodes,
+and virtualization infrastructure are available [upon
+request](https://support.it4i.cz/rt) made by a PI.
+
+Schematic representation of the Anselm cluster. Each box represents a
+node (computer) or storage capacity:
+
+User-oriented infrastructure
+Storage
+Management infrastructure
+ --------
+ login1
+ login2
+ dm1
+ --------
+
+Rack 01, Switch isw5
+
+ -------- |---|---|---- -------------- -------------- --------------
+ cn186 cn187 cn188 cn189
+ cn181 cn182 cn183 cn184 cn185
+ -------- |---|---|---- -------------- -------------- --------------
+
+Rack 01, Switch isw4
+
+cn29
+cn30
+cn31
+cn32
+cn33
+cn34
+cn35
+cn36
+cn19
+cn20
+cn21
+cn22
+cn23
+cn24
+cn25
+cn26
+cn27
+cn28
+<col width="100%" />
+ |Â <p>Â <p>Lustre FS<p>/home320TB<p>Â <p>Â \ |
+ |Lustre FS<p>/scratch146TB\ |
+
+Management
+nodes
+Block storage
+45 TB
+Virtualization
+infrastructure
+servers
+...
+Srv node
+Srv node
+Srv node
+...
+Rack 01, Switch isw0
+
+cn11
+cn12
+cn13
+cn14
+cn15
+cn16
+cn17
+cn18
+cn1
+cn2
+cn3
+cn4
+cn5
+cn6
+cn7
+cn8
+cn9
+cn10
+Rack 02, Switch isw10
+
+cn73
+cn74
+cn75
+cn76
+cn77
+cn78
+cn79
+cn80
+cn190
+cn191
+cn192
+cn205
+cn206
+Rack 02, Switch isw9
+
+cn65
+cn66
+cn67
+cn68
+cn69
+cn70
+cn71
+cn72
+cn55
+cn56
+cn57
+cn58
+cn59
+cn60
+cn61
+cn62
+cn63
+cn64
+Rack 02, Switch isw6
+
+cn47
+cn48
+cn49
+cn50
+cn51
+cn52
+cn53
+cn54
+cn37
+cn38
+cn39
+cn40
+cn41
+cn42
+cn43
+cn44
+cn45
+cn46
+Rack 03, Switch isw15
+
+cn193
+cn194
+cn195
+cn207
+cn117
+cn118
+cn119
+cn120
+cn121
+cn122
+cn123
+cn124
+cn125
+cn126
+Rack 03, Switch isw14
+
+cn109
+cn110
+cn111
+cn112
+cn113
+cn114
+cn115
+cn116
+cn99
+cn100
+cn101
+cn102
+cn103
+cn104
+cn105
+cn106
+cn107
+cn108
+Rack 03, Switch isw11
+
+cn91
+cn92
+cn93
+cn94
+cn95
+cn96
+cn97
+cn98
+cn81
+cn82
+cn83
+cn84
+cn85
+cn86
+cn87
+cn88
+cn89
+cn90
+Rack 04, Switch isw20
+
+cn173
+cn174
+cn175
+cn176
+cn177
+cn178
+cn179
+cn180
+cn163
+cn164
+cn165
+cn166
+cn167
+cn168
+cn169
+cn170
+cn171
+cn172
+Rack 04, **Switch** isw19
+
+cn155
+cn156
+cn157
+cn158
+cn159
+cn160
+cn161
+cn162
+cn145
+cn146
+cn147
+cn148
+cn149
+cn150
+cn151
+cn152
+cn153
+cn154
+Rack 04, Switch isw16
+
+cn137
+cn138
+cn139
+cn140
+cn141
+cn142
+cn143
+cn144
+cn127
+cn128
+cn129
+cn130
+cn131
+cn132
+cn133
+cn134
+cn135
+cn136
+Rack 05, Switch isw21
+
+ -------- |---|---|---- -------------- -------------- --------------
+ cn201 cn202 cn203 cn204
+ cn196 cn197 cn198 cn199 cn200
+ -------- |---|---|---- -------------- -------------- --------------
+
+ ----------------
+ Fat node cn208
+ Fat node cn209
+ ...
+ ----------------
+
+The cluster compute nodes cn[1-207] are organized within 13 chassis.Â
+
+There are four types of compute nodes:
+
+- 180 compute nodes without the accelerator
+- 23 compute nodes with GPU accelerator - equipped with NVIDIA Tesla
+ Kepler K20
+- 4Â compute nodes with MIC accelerator - equipped with Intel Xeon Phi
+ 5110P
+- 2 fat nodes - equipped with 512GB RAM and two 100GB SSD drives
+
+[More about Compute nodes](compute-nodes.html).
+
+GPU and accelerated nodes are available upon request, see the [Resources
+Allocation
+Policy](resource-allocation-and-job-execution/resources-allocation-policy.html).
+
+All these nodes are interconnected by fast
+InfiniBand class="WYSIWYG_LINK">QDR
+network and Ethernet network. [More about the
+Network](network.html).
+Every chassis provides Infiniband switch, marked **isw**, connecting all
+nodes in the chassis, as well as connecting the chassis to the upper
+level switches.
+
+All nodes share 360TB /home disk storage to store user files. The 146TB
+shared /scratch storage is available for the scratch data. These file
+systems are provided by Lustre parallel file system. There is also local
+disk storage available on all compute nodes /lscratch. [More about
+
+Storage](storage.html).
+
+The user access to the Anselm cluster is provided by two login nodes
+login1, login2, and data mover node dm1. [More about accessing
+cluster.](accessing-the-cluster.html)
+
+Â The parameters are summarized in the following tables:
+
+In general**
+Primary purpose
+High Performance Computing
+Architecture of compute nodes
+x86-64
+Operating system
+Linux
+[**Compute nodes**](compute-nodes.html)
+Totally
+209
+Processor cores
+16 (2x8 cores)
+RAM
+min. 64 GB, min. 4 GB per core
+Local disk drive
+yes - usually 500 GB
+Compute network
+InfiniBand QDR, fully non-blocking, fat-tree
+w/o accelerator
+180, cn[1-180]
+GPU accelerated
+23, cn[181-203]
+MIC accelerated
+4, cn[204-207]
+Fat compute nodes
+2, cn[208-209]
+In total**
+Total theoretical peak performance (Rpeak)
+94 Tflop/s
+Total max. LINPACK performance (Rmax)
+73 Tflop/s
+Total amount of RAM
+15.136 TB
+ |Node|Processor|Memory|Accelerator|
+ |---|---|---|---|
+ |w/o accelerator|2x Intel Sandy Bridge E5-2665, 2.4GHz|64GB|-|
+ |GPU accelerated|2x Intel Sandy Bridge E5-2470, 2.3GHz|96GB|NVIDIA Kepler K20|
+ |MIC accelerated|2x Intel Sandy Bridge E5-2470, 2.3GHz|96GB|Intel Xeon Phi P5110|
+ |Fat compute node|2x Intel Sandy Bridge E5-2665, 2.4GHz|512GB|-|
+
+Â For more details please refer to the [Compute
+nodes](compute-nodes.html),
+[Storage](storage.html), and
+[Network](network.html).
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/introduction.md b/converted/docs.it4i.cz/anselm-cluster-documentation/introduction.md
new file mode 100644
index 0000000000000000000000000000000000000000..68a2e10aa3b2079f2fb1dce3b25653fb7f494ccc
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/introduction.md
@@ -0,0 +1,39 @@
+Introduction
+============
+
+
+
+Welcome to Anselm supercomputer cluster. The Anselm cluster consists of
+209 compute nodes, totaling 3344 compute cores with 15TB RAM and giving
+over 94 Tflop/s theoretical peak performance. Each node is a
+powerful x86-64 computer, equipped with 16
+cores, at least 64GB RAM, and 500GB harddrive. Nodes are interconnected
+by fully non-blocking fat-tree Infiniband network and equipped with
+Intel Sandy Bridge processors. A few nodes are also equipped with NVIDIA
+Kepler GPU or Intel Xeon Phi MIC accelerators. Read more in [Hardware
+Overview](hardware-overview.html).
+
+The cluster runs bullx Linux [
+](http://www.bull.com/bullx-logiciels/systeme-exploitation.html)[operating
+system](software/operating-system.html), which is
+compatible with the RedHat [
+Linux
+family.](http://upload.wikimedia.org/wikipedia/commons/1/1b/Linux_Distribution_Timeline.svg)
+We have installed a wide range of
+[software](software.1.html) packages targeted at
+different scientific domains. These packages are accessible via the
+[modules environment](environment-and-modules.html).
+
+User data shared file-system (HOME, 320TB) and job data shared
+file-system (SCRATCH, 146TB) are available to users.
+
+The PBS Professional workload manager provides [computing resources
+allocations and job
+execution](resource-allocation-and-job-execution.html).
+
+Read more on how to [apply for
+resources](../get-started-with-it4innovations/applying-for-resources.html),
+[obtain login
+credentials,](../get-started-with-it4innovations/obtaining-login-credentials.html)
+and [access the cluster](accessing-the-cluster.html).
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/legend.png b/converted/docs.it4i.cz/anselm-cluster-documentation/legend.png
new file mode 100644
index 0000000000000000000000000000000000000000..2950ff1bd7059f93195437476fa9333ec42da408
Binary files /dev/null and b/converted/docs.it4i.cz/anselm-cluster-documentation/legend.png differ
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/network.md b/converted/docs.it4i.cz/anselm-cluster-documentation/network.md
new file mode 100644
index 0000000000000000000000000000000000000000..b897039fe15a2ddc1374459f610af810a773f42a
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/network.md
@@ -0,0 +1,58 @@
+Network
+=======
+
+
+
+All compute and login nodes of Anselm are interconnected by
+[Infiniband](http://en.wikipedia.org/wiki/InfiniBand)
+QDR network and by Gigabit
+[Ethernet](http://en.wikipedia.org/wiki/Ethernet)
+network. Both networks may be used to transfer user data.
+
+Infiniband Network
+------------------
+
+All compute and login nodes of Anselm are interconnected by a
+high-bandwidth, low-latency
+[Infiniband](http://en.wikipedia.org/wiki/InfiniBand)
+QDR network (IB 4x QDR, 40 Gbps). The network topology is a fully
+non-blocking fat-tree.
+
+The compute nodes may be accessed via the Infiniband network using ib0
+network interface, in address range 10.2.1.1-209. The MPI may be used to
+establish native Infiniband connection among the nodes.
+
+The network provides **2170MB/s** transfer rates via the TCP connection
+(single stream) and up to **3600MB/s** via native Infiniband protocol.
+
+The Fat tree topology ensures that peak transfer rates are achieved
+between any two nodes, independent of network traffic exchanged among
+other nodes concurrently.
+
+Ethernet Network
+----------------
+
+The compute nodes may be accessed via the regular Gigabit Ethernet
+network interface eth0, in address range 10.1.1.1-209, or by using
+aliases cn1-cn209.
+The network provides **114MB/s** transfer rates via the TCP connection.
+
+Example
+-------
+
+`
+$ qsub -q qexp -l select=4:ncpus=16 -N Name0 ./myjob
+$ qstat -n -u username
+ Req'd Req'd Elap
+Job ID Username Queue Jobname SessID NDS TSK Memory Time S Time
+--------------- -------- -- |---|---| ------ --- --- ------ ----- - -----
+15209.srv11 username qexp Name0 5530 4 64 -- 01:00 R 00:00
+ cn17/0*16+cn108/0*16+cn109/0*16+cn110/0*16
+
+$ ssh 10.2.1.110
+$ ssh 10.1.1.108
+`
+
+In this example, we access the node cn110 by Infiniband network via the
+ib0 interface, then from cn110 to cn108 by Ethernet network.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/prace.md b/converted/docs.it4i.cz/anselm-cluster-documentation/prace.md
new file mode 100644
index 0000000000000000000000000000000000000000..9d29c080f0a885c9022254e5024020f52f0304ba
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/prace.md
@@ -0,0 +1,374 @@
+PRACE User Support
+==================
+
+
+
+Intro
+-----
+
+PRACE users coming to Anselm as to TIER-1 system offered through the
+DECI calls are in general treated as standard users and so most of the
+general documentation applies to them as well. This section shows the
+main differences for quicker orientation, but often uses references to
+the original documentation. PRACE users who don't undergo the full
+procedure (including signing the IT4I AuP on top of the PRACE AuP) will
+not have a password and thus access to some services intended for
+regular users. This can lower their comfort, but otherwise they should
+be able to use the TIER-1 system as intended. Please see the [Obtaining
+Login Credentials
+section](../get-started-with-it4innovations/obtaining-login-credentials/obtaining-login-credentials.html),
+if the same level of access is required.
+
+All general [PRACE User
+Documentation](http://www.prace-ri.eu/user-documentation/)
+should be read before continuing reading the local documentation here.
+
+Help and Support
+--------------------
+
+If you have any troubles, need information, request support or want to
+install additional software, please use [PRACE
+Helpdesk](http://www.prace-ri.eu/helpdesk-guide264/).
+
+Information about the local services are provided in the [introduction
+of general user documentation](introduction.html).
+Please keep in mind, that standard PRACE accounts don't have a password
+to access the web interface of the local (IT4Innovations) request
+tracker and thus a new ticket should be created by sending an e-mail to
+support[at]it4i.cz.
+
+Obtaining Login Credentials
+---------------------------
+
+In general PRACE users already have a PRACE account setup through their
+HOMESITE (institution from their country) as a result of rewarded PRACE
+project proposal. This includes signed PRACE AuP, generated and
+registered certificates, etc.
+
+If there's a special need a PRACE user can get a standard (local)
+account at IT4Innovations. To get an account on the Anselm cluster, the
+user needs to obtain the login credentials. The procedure is the same as
+for general users of the cluster, so please see the corresponding
+[section of the general documentation
+here](../get-started-with-it4innovations/obtaining-login-credentials.html).
+
+Accessing the cluster
+---------------------
+
+### Access with GSI-SSH
+
+For all PRACE users the method for interactive access (login) and data
+transfer based on grid services from Globus Toolkit (GSI SSH and
+GridFTP) is supported.
+
+The user will need a valid certificate and to be present in the PRACE
+LDAP (please contact your HOME SITE or the primary investigator of your
+project for LDAP account creation).
+
+Most of the information needed by PRACE users accessing the Anselm
+TIER-1 system can be found here:
+
+- [General user's
+ FAQ](http://www.prace-ri.eu/Users-General-FAQs)
+- [Certificates
+ FAQ](http://www.prace-ri.eu/Certificates-FAQ)
+- [Interactive access using
+ GSISSH](http://www.prace-ri.eu/Interactive-Access-Using-gsissh)
+- [Data transfer with
+ GridFTP](http://www.prace-ri.eu/Data-Transfer-with-GridFTP-Details)
+- [Data transfer with
+ gtransfer](http://www.prace-ri.eu/Data-Transfer-with-gtransfer)
+
+Â
+
+Before you start to use any of the services don't forget to create a
+proxy certificate from your certificate:
+
+ $ grid-proxy-init
+
+To check whether your proxy certificate is still valid (by default it's
+valid 12 hours), use:
+
+ $ grid-proxy-info
+
+Â
+
+To access Anselm cluster, two login nodes running GSI SSH service are
+available. The service is available from public Internet as well as from
+the internal PRACE network (accessible only from other PRACE partners).
+
+***Access from PRACE network:**
+
+It is recommended to use the single DNS name
+anselm-prace.it4i.cz which is distributed
+between the two login nodes. If needed, user can login directly to one
+of the login nodes. The addresses are:
+
+ Login address |Port|Protocol| Login node
+ ----------------------------- |---|---| ------------------
+ anselm-prace.it4i.cz 2222 gsissh login1 or login2
+ login1-prace.anselm.it4i.cz 2222 gsissh login1
+ login2-prace.anselm.it4i.cz 2222 gsissh login2
+
+Â
+
+ $ gsissh -p 2222 anselm-prace.it4i.cz
+
+When logging from other PRACE system, the prace_service script can be
+used:
+
+ $ gsissh `prace_service -i -s anselm`
+
+Â
+
+***Access from public Internet:**
+
+It is recommended to use the single DNS name
+anselm.it4i.cz which is distributed between the
+two login nodes. If needed, user can login directly to one of the login
+nodes. The addresses are:
+
+ Login address |Port|Protocol| Login node
+ ----------------------- |---|---| ------------------
+ anselm.it4i.cz 2222 gsissh login1 or login2
+ login1.anselm.it4i.cz 2222 gsissh login1
+ login2.anselm.it4i.cz 2222 gsissh login2
+
+ $ gsissh -p 2222 anselm.it4i.cz
+
+When logging from other PRACE system, the
+prace_service script can be used:
+
+ $ gsissh `prace_service -e -s anselm`
+
+Â
+
+Although the preferred and recommended file transfer mechanism is [using
+GridFTP](prace.html#file-transfers), the GSI SSH
+implementation on Anselm supports also SCP, so for small files transfer
+gsiscp can be used:
+
+ $ gsiscp -P 2222 _LOCAL_PATH_TO_YOUR_FILE_ anselm.it4i.cz:_ANSELM_PATH_TO_YOUR_FILE_
+
+ $ gsiscp -P 2222 anselm.it4i.cz:_ANSELM_PATH_TO_YOUR_FILE_ _LOCAL_PATH_TO_YOUR_FILE_
+
+ $ gsiscp -P 2222 _LOCAL_PATH_TO_YOUR_FILE_ anselm-prace.it4i.cz:_ANSELM_PATH_TO_YOUR_FILE_
+
+ $ gsiscp -P 2222 anselm-prace.it4i.cz:_ANSELM_PATH_TO_YOUR_FILE_ _LOCAL_PATH_TO_YOUR_FILE_
+
+### Access to X11 applications (VNC)
+
+If the user needs to run X11 based graphical application and does not
+have a X11 server, the applications can be run using VNC service. If the
+user is using regular SSH based access, please see the [section in
+general
+documentation](https://docs.it4i.cz/anselm-cluster-documentation/resolveuid/11e53ad0d2fd4c5187537f4baeedff33).
+
+If the user uses GSI SSH based access, then the procedure is similar to
+the SSH based access ([look
+here](https://docs.it4i.cz/anselm-cluster-documentation/resolveuid/11e53ad0d2fd4c5187537f4baeedff33)),
+only the port forwarding must be done using GSI SSH:
+
+ $ gsissh -p 2222 anselm.it4i.cz -L 5961:localhost:5961
+
+### Access with SSH
+
+After successful obtainment of login credentials for the local
+IT4Innovations account, the PRACE users can access the cluster as
+regular users using SSH. For more information please see the [section in
+general
+documentation](https://docs.it4i.cz/anselm-cluster-documentation/resolveuid/5d3d6f3d873a42e584cbf4365c4e251b).
+
+File transfers
+------------------
+
+PRACE users can use the same transfer mechanisms as regular users (if
+they've undergone the full registration procedure). For information
+about this, please see [the section in the general
+documentation](https://docs.it4i.cz/anselm-cluster-documentation/resolveuid/5d3d6f3d873a42e584cbf4365c4e251b).
+
+Apart from the standard mechanisms, for PRACE users to transfer data
+to/from Anselm cluster, a GridFTP server running Globus Toolkit GridFTP
+service is available. The service is available from public Internet as
+well as from the internal PRACE network (accessible only from other
+PRACE partners).
+
+There's one control server and three backend servers for striping and/or
+backup in case one of them would fail.
+
+***Access from PRACE network:**
+
+ Login address Port Node role
+ ----- |---|---|
+ gridftp-prace.anselm.it4i.cz 2812 Front end /control server
+ login1-prace.anselm.it4i.cz 2813 Backend / data mover server
+ login2-prace.anselm.it4i.cz 2813 Backend / data mover server
+ dm1-prace.anselm.it4i.cz 2813 Backend / data mover server
+
+Copy files **to** Anselm by running the following commands on your local
+machine:
+
+ $ globus-url-copy file://_LOCAL_PATH_TO_YOUR_FILE_ gsiftp://gridftp-prace.anselm.it4i.cz:2812/home/prace/_YOUR_ACCOUNT_ON_ANSELM_/_PATH_TO_YOUR_FILE_
+
+Or by using prace_service script:
+
+ $ globus-url-copy file://_LOCAL_PATH_TO_YOUR_FILE_ gsiftp://`prace_service -i -f anselm`/home/prace/_YOUR_ACCOUNT_ON_ANSELM_/_PATH_TO_YOUR_FILE_
+
+Copy files **from** Anselm:
+
+ $ globus-url-copy gsiftp://gridftp-prace.anselm.it4i.cz:2812/home/prace/_YOUR_ACCOUNT_ON_ANSELM_/_PATH_TO_YOUR_FILE_ file://_LOCAL_PATH_TO_YOUR_FILE_
+
+Or by using prace_service script:
+
+ $ globus-url-copy gsiftp://`prace_service -i -f anselm`/home/prace/_YOUR_ACCOUNT_ON_ANSELM_/_PATH_TO_YOUR_FILE_ file://_LOCAL_PATH_TO_YOUR_FILE_
+
+Â
+
+***Access from public Internet:**
+
+ Login address Port Node role
+ ------------------------ |---|---|-------------------
+ gridftp.anselm.it4i.cz 2812 Front end /control server
+ login1.anselm.it4i.cz 2813 Backend / data mover server
+ login2.anselm.it4i.cz 2813 Backend / data mover server
+ dm1.anselm.it4i.cz 2813 Backend / data mover server
+
+Copy files **to** Anselm by running the following commands on your local
+machine:
+
+ $ globus-url-copy file://_LOCAL_PATH_TO_YOUR_FILE_ gsiftp://gridftp.anselm.it4i.cz:2812/home/prace/_YOUR_ACCOUNT_ON_ANSELM_/_PATH_TO_YOUR_FILE_
+
+Or by using prace_service script:
+
+ $ globus-url-copy file://_LOCAL_PATH_TO_YOUR_FILE_ gsiftp://`prace_service -e -f anselm`/home/prace/_YOUR_ACCOUNT_ON_ANSELM_/_PATH_TO_YOUR_FILE_
+
+Copy files **from** Anselm:
+
+ $ globus-url-copy gsiftp://gridftp.anselm.it4i.cz:2812/home/prace/_YOUR_ACCOUNT_ON_ANSELM_/_PATH_TO_YOUR_FILE_ file://_LOCAL_PATH_TO_YOUR_FILE_
+
+Or by using prace_service script:
+
+ $ globus-url-copy gsiftp://`prace_service -e -f anselm`/home/prace/_YOUR_ACCOUNT_ON_ANSELM_/_PATH_TO_YOUR_FILE_ file://_LOCAL_PATH_TO_YOUR_FILE_
+
+Â
+
+Generally both shared file systems are available through GridFTP:
+
+ |File system mount point|Filesystem|Comment|
+ |---|---|
+ |/home|Lustre|Default HOME directories of users in format /home/prace/login/|
+ |/scratch|Lustre|Shared SCRATCH mounted on the whole cluster|
+
+More information about the shared file systems is available
+[here](storage.html).
+
+Usage of the cluster
+--------------------
+
+There are some limitations for PRACE user when using the cluster. By
+default PRACE users aren't allowed to access special queues in the PBS
+Pro to have high priority or exclusive access to some special equipment
+like accelerated nodes and high memory (fat) nodes. There may be also
+restrictions obtaining a working license for the commercial software
+installed on the cluster, mostly because of the license agreement or
+because of insufficient amount of licenses.
+
+For production runs always use scratch file systems, either the global
+shared or the local ones. The available file systems are described
+[here](hardware-overview.html).
+
+### Software, Modules and PRACE Common Production Environment
+
+All system wide installed software on the cluster is made available to
+the users via the modules. The information about the environment and
+modules usage is in this [section of general
+documentation](environment-and-modules.html).
+
+PRACE users can use the "prace" module to use the [PRACE Common
+Production
+Environment](http://www.prace-ri.eu/PRACE-common-production).
+
+ $ module load prace
+
+Â
+
+### Resource Allocation and Job Execution
+
+General information about the resource allocation, job queuing and job
+execution is in this [section of general
+documentation](resource-allocation-and-job-execution/introduction.html).
+
+For PRACE users, the default production run queue is "qprace". PRACE
+users can also use two other queues "qexp" and "qfree".
+
+ -------------------------------------------------------------------------------------------------------------------------
+ queue Active project Project resources Nodes priority authorization walltime
+
+ --------------------- -|---|---|---|- ---- |---|---|----- -------------
+ **qexp** no none required 2 reserved, high no 1 / 1h
+ \ 8 total
+
+ gt; 0 >1006 nodes, max 86 per job 0 no 24 / 48h> 0 178 w/o accelerator medium no 24 / 48h
+ \
+
+
+ **qfree** yes none required 178 w/o accelerator very low no 12 / 12h
+ \
+ -------------------------------------------------------------------------------------------------------------------------
+
+qprace**, the PRACE \***: This queue is intended for
+normal production runs. It is required that active project with nonzero
+remaining resources is specified to enter the qprace. The queue runs
+with medium priority and no special authorization is required to use it.
+The maximum runtime in qprace is 12 hours. If the job needs longer time,
+it must use checkpoint/restart functionality.
+
+### Accounting & Quota
+
+The resources that are currently subject to accounting are the core
+hours. The core hours are accounted on the wall clock basis. The
+accounting runs whenever the computational cores are allocated or
+blocked via the PBS Pro workload manager (the qsub command), regardless
+of whether the cores are actually used for any calculation. See [example
+in the general
+documentation](resource-allocation-and-job-execution/resources-allocation-policy.html).
+
+PRACE users should check their project accounting using the [PRACE
+Accounting Tool
+(DART)](http://www.prace-ri.eu/accounting-report-tool/).
+
+Users who have undergone the full local registration procedure
+(including signing the IT4Innovations Acceptable Use Policy) and who
+have received local password may check at any time, how many core-hours
+have been consumed by themselves and their projects using the command
+"it4ifree". Please note that you need to know your user password to use
+the command and that the displayed core hours are "system core hours"
+which differ from PRACE "standardized core hours".
+
+The **it4ifree** command is a part of it4i.portal.clients package,
+located here:
+<https://pypi.python.org/pypi/it4i.portal.clients>
+
+ $ it4ifree
+ Password:
+     PID  Total Used ...by me Free
+ Â Â -------- ------- ------ -------- -------
+ Â Â OPEN-0-0 1500000 400644Â Â 225265 1099356
+ Â Â DD-13-1 Â Â 10000 2606 2606 7394
+
+Â
+
+By default file system quota is applied. To check the current status of
+the quota use
+
+ $ lfs quota -u USER_LOGIN /home
+ $ lfs quota -u USER_LOGIN /scratch
+
+If the quota is insufficient, please contact the
+[support](prace.html#help-and-support) and request an
+increase.
+
+Â
+
+Â
+
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+Remote visualization service
+============================
+
+Introduction
+------------
+
+The goal of this service is to provide the users a GPU accelerated use
+of OpenGL applications, especially for pre- and post- processing work,
+where not only the GPU performance is needed but also fast access to the
+shared file systems of the cluster and a reasonable amount of RAM.
+
+The service is based on integration of open source tools VirtualGL and
+TurboVNC together with the cluster's job scheduler PBS Professional.
+
+Currently two compute nodes are dedicated for this service with
+following configuration for each node:
+
+[**Visualization node
+configuration**](compute-nodes.html)
+CPU
+2x Intel Sandy Bridge E5-2670, 2.6GHz
+Processor cores
+16 (2x8 cores)
+RAM
+64 GB, min. 4 GB per core
+GPU
+NVIDIA Quadro 4000, 2GB RAM
+Local disk drive
+yes - 500 GB
+Compute network
+InfiniBand QDR
+Schematic overview
+------------------
+
+
+
+
+
+How to use the service
+----------------------
+
+### Setup and start your own TurboVNC server.
+
+TurboVNC is designed and implemented for cooperation with VirtualGL and
+available for free for all major platforms. For more information and
+download, please refer to: <http://sourceforge.net/projects/turbovnc/>
+
+Always use TurboVNC on both sides** (server and client) **don't mix
+TurboVNC and other VNC implementations** (TightVNC, TigerVNC, ...) as
+the VNC protocol implementation may slightly differ and diminish your
+user experience by introducing picture artifacts, etc.
+
+The procedure is:
+
+#### 1. Connect to a login node. {#1-connect-to-a-login-node}
+
+Please [follow the
+documentation](https://docs.it4i.cz/anselm-cluster-documentation/resolveuid/5d3d6f3d873a42e584cbf4365c4e251b).
+
+#### 2. Run your own instance of TurboVNC server. {#2-run-your-own-instance-of-turbovnc-server}
+
+To have the OpenGL acceleration, **24 bit color depth must be used**.
+Otherwise only the geometry (desktop size) definition is needed.
+
+*At first VNC server run you need to define a password.*
+
+This example defines desktop with dimensions 1200x700 pixels and 24 bit
+color depth.
+
+`
+$ module load turbovnc/1.2.2
+$ vncserver -geometry 1200x700 -depth 24
+
+Desktop 'TurboVNC: login2:1 (username)' started on display login2:1
+
+Starting applications specified in /home/username/.vnc/xstartup.turbovnc
+Log file is /home/username/.vnc/login2:1.log
+`
+
+#### 3. Remember which display number your VNC server runs (you will need it in the future to stop the server). {#3-remember-which-display-number-your-vnc-server-runs-you-will-need-it-in-the-future-to-stop-the-server}
+
+`
+$ vncserver -list
+
+TurboVNC server sessions:
+
+X DISPLAY # PROCESS ID
+:1 23269
+`
+
+In this example the VNC server runs on display **:1**.
+
+#### 4. Remember the exact login node, where your VNC server runs. {#4-remember-the-exact-login-node-where-your-vnc-server-runs}
+
+`
+$ uname -n
+login2
+`
+
+In this example the VNC server runs on **login2**.
+
+#### 5. Remember on which TCP port your own VNC server is running. {#5-remember-on-which-tcp-port-your-own-vnc-server-is-running}
+
+To get the port you have to look to the log file of your VNC server.
+
+`
+$ grep -E "VNC.*port" /home/username/.vnc/login2:1.log
+20/02/2015 14:46:41 Listening for VNC connections on TCP port 5901
+`
+
+In this example the VNC server listens on TCP port **5901**.
+
+#### 6. Connect to the login node where your VNC server runs with SSH to tunnel your VNC session. {#6-connect-to-the-login-node-where-your-vnc-server-runs-with-ssh-to-tunnel-your-vnc-session}
+
+Tunnel the TCP port on which your VNC server is listenning.
+
+`
+$ ssh login2.anselm.it4i.cz -L 5901:localhost:5901
+`
+
+*If you use Windows and Putty, please refer to port forwarding setup
+ in the documentation:*
+[https://docs.it4i.cz/anselm-cluster-documentation/accessing-the-cluster/x-window-and-vnc#section-12](accessing-the-cluster/x-window-and-vnc.html#section-12)
+
+#### 7. If you don't have Turbo VNC installed on your workstation. {#7-if-you-don-t-have-turbo-vnc-installed-on-your-workstation}
+
+Get it from: <http://sourceforge.net/projects/turbovnc/>
+
+#### 8. Run TurboVNC Viewer from your workstation. {#8-run-turbovnc-viewer-from-your-workstation}
+
+Mind that you should connect through the SSH tunneled port. In this
+example it is 5901 on your workstation (localhost).
+
+`
+$ vncviewer localhost:5901
+`
+
+*If you use Windows version of TurboVNC Viewer, just run the Viewer and
+use address **localhost:5901**.*
+
+#### 9. Proceed to the chapter "Access the visualization node." {#9-proceed-to-the-chapter-access-the-visualization-node}
+
+*Now you should have working TurboVNC session connected to your
+workstation.*
+
+#### 10. After you end your visualization session. {#10-after-you-end-your-visualization-session}
+
+*Don't forget to correctly shutdown your own VNC server on the login
+node!*
+
+`
+$ vncserver -kill :1
+`
+
+Access the visualization node
+-----------------------------
+
+To access the node use a dedicated PBS Professional scheduler queue
+qviz**. The queue has following properties:
+
+ |queue |active project |project resources |nodes<th align="left">min ncpus*<th align="left">priority<th align="left">authorization<th align="left">walltime |
+ | --- | --- |
+ |<strong>qviz              </strong> Visualization queue\ |yes |none required |2 |4 |><em>150</em> |no |1 hour / 2 hours |
+
+Currently when accessing the node, each user gets 4 cores of a CPU
+allocated, thus approximately 16 GB of RAM and 1/4 of the GPU capacity.
+*If more GPU power or RAM is required, it is recommended to allocate one
+whole node per user, so that all 16 cores, whole RAM and whole GPU is
+exclusive. This is currently also the maximum allowed allocation per one
+user. One hour of work is allocated by default, the user may ask for 2
+hours maximum.*
+
+To access the visualization node, follow these steps:
+
+#### 1. In your VNC session, open a terminal and allocate a node using PBSPro qsub command. {#1-in-your-vnc-session-open-a-terminal-and-allocate-a-node-using-pbspro-qsub-command}
+
+*This step is necessary to allow you to proceed with next steps.*
+
+`
+$ qsub -I -q qviz -A PROJECT_ID
+`
+
+In this example the default values for CPU cores and usage time are
+used.
+
+`
+$ qsub -I -q qviz -A PROJECT_ID -l select=1:ncpus=16 -l walltime=02:00:00
+`
+
+*Substitute **PROJECT_ID** with the assigned project identification
+string.*
+
+In this example a whole node for 2 hours is requested.
+
+If there are free resources for your request, you will have a shell
+running on an assigned node. Please remember the name of the node.
+
+`
+$ uname -n
+srv8
+`
+
+In this example the visualization session was assigned to node **srv8**.
+
+#### 2. In your VNC session open another terminal (keep the one with interactive PBSPro job open). {#2-in-your-vnc-session-open-another-terminal-keep-the-one-with-interactive-pbspro-job-open}
+
+Setup the VirtualGL connection to the node, which PBSPro allocated for
+your job.
+
+`
+$ vglconnect srv8
+`
+
+You will be connected with created VirtualGL tunnel to the visualization
+node, where you will have a shell.
+
+#### 3. Load the VirtualGL module. {#3-load-the-virtualgl-module}
+
+`
+$ module load virtualgl/2.4
+`
+
+#### 4. Run your desired OpenGL accelerated application using VirtualGL script "vglrun". {#4-run-your-desired-opengl-accelerated-application-using-virtualgl-script-vglrun}
+
+`
+$ vglrun glxgears
+`
+
+Please note, that if you want to run an OpenGL application which is
+available through modules, you need at first load the respective module.
+E. g. to run the **Mentat** OpenGL application from **MARC** software
+package use:
+
+`
+$ module load marc/2013.1
+$ vglrun mentat
+`
+
+#### 5. After you end your work with the OpenGL application. {#5-after-you-end-your-work-with-the-opengl-application}
+
+Just logout from the visualization node and exit both opened terminals
+and end your VNC server session as described above.
+
+Tips and Tricks
+---------------
+
+If you want to increase the responsibility of the visualization, please
+adjust your TurboVNC client settings in this way:
+
+
+
+To have an idea how the settings are affecting the resulting picture
+quality three levels of "JPEG image quality" are demonstrated:
+
+1. JPEG image quality = 30
+
+
+
+2. JPEG image quality = 15
+
+
+
+3. JPEG image quality = 10
+
+
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/resource-allocation-and-job-execution/capacity-computing.md b/converted/docs.it4i.cz/anselm-cluster-documentation/resource-allocation-and-job-execution/capacity-computing.md
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+Capacity computing
+==================
+
+
+
+Introduction
+------------
+
+In many cases, it is useful to submit huge (>100+) number of
+computational jobs into the PBS queue system. Huge number of (small)
+jobs is one of the most effective ways to execute embarrassingly
+parallel calculations, achieving best runtime, throughput and computer
+utilization.
+
+However, executing huge number of jobs via the PBS queue may strain the
+system. This strain may result in slow response to commands, inefficient
+scheduling and overall degradation of performance and user experience,
+for all users. For this reason, the number of jobs is **limited to 100
+per user, 1000 per job array**
+
+Please follow one of the procedures below, in case you wish to schedule
+more than >100 jobs at a time.
+
+- Use [Job arrays](capacity-computing.html#job-arrays)
+ when running huge number of
+ [multithread](capacity-computing.html#shared-jobscript-on-one-node)
+ (bound to one node only) or multinode (multithread across
+ several nodes) jobs
+- Use [GNU
+ parallel](capacity-computing.html#gnu-parallel) when
+ running single core jobs
+- Combine[GNU parallel with Job
+ arrays](capacity-computing.html#combining-job-arrays-and-gnu-parallel)Â
+ when running huge number of single core jobs
+
+Policy
+------
+
+1. A user is allowed to submit at most 100 jobs. Each job may be [a job
+ array](capacity-computing.html#job-arrays).
+2. The array size is at most 1000 subjobs.
+
+Job arrays
+--------------
+
+Huge number of jobs may be easily submitted and managed as a job array.
+
+A job array is a compact representation of many jobs, called subjobs.
+The subjobs share the same job script, and have the same values for all
+attributes and resources, with the following exceptions:
+
+- each subjob has a unique index, $PBS_ARRAY_INDEX
+- job Identifiers of subjobs only differ by their indices
+- the state of subjobs can differ (R,Q,...etc.)
+
+All subjobs within a job array have the same scheduling priority and
+schedule as independent jobs.
+Entire job array is submitted through a single qsub command and may be
+managed by qdel, qalter, qhold, qrls and qsig commands as a single job.
+
+### Shared jobscript
+
+All subjobs in job array use the very same, single jobscript. Each
+subjob runs its own instance of the jobscript. The instances execute
+different work controlled by $PBS_ARRAY_INDEX variable.
+
+Example:
+
+Assume we have 900 input files with name beginning with "file" (e. g.
+file001, ..., file900). Assume we would like to use each of these input
+files with program executable myprog.x, each as a separate job.
+
+First, we create a tasklist file (or subjobs list), listing all tasks
+(subjobs) - all input files in our example:
+
+`
+$ find . -name 'file*' > tasklist
+`
+
+Then we create jobscript:
+
+`
+#!/bin/bash
+#PBS -A PROJECT_ID
+#PBS -q qprod
+#PBS -l select=1:ncpus=16,walltime=02:00:00
+
+# change to local scratch directory
+SCR=/lscratch/$PBS_JOBID
+mkdir -p $SCR ; cd $SCR || exit
+
+# get individual tasks from tasklist with index from PBS JOB ARRAY
+TASK=$(sed -n "${PBS_ARRAY_INDEX}p" $PBS_O_WORKDIR/tasklist)
+
+# copy input file and executable to scratch
+cp $PBS_O_WORKDIR/$TASK input ; cp $PBS_O_WORKDIR/myprog.x .
+
+# execute the calculation
+./myprog.x < input > output
+
+# copy output file to submit directory
+cp output $PBS_O_WORKDIR/$TASK.out
+`
+
+In this example, the submit directory holds the 900 input files,
+executable myprog.x and the jobscript file. As input for each run, we
+take the filename of input file from created tasklist file. We copy the
+input file to local scratch /lscratch/$PBS_JOBID, execute the myprog.x
+and copy the output file back to >the submit directory,
+under the $TASK.out name. The myprog.x runs on one node only and must
+use threads to run in parallel. Be aware, that if the myprog.x **is not
+multithreaded**, then all the **jobs are run as single thread programs
+in sequential** manner. Due to allocation of the whole node, the
+accounted time is equal to the usage of whole node**, while using only
+1/16 of the node!
+
+If huge number of parallel multicore (in means of multinode multithread,
+e. g. MPI enabled) jobs is needed to run, then a job array approach
+should also be used. The main difference compared to previous example
+using one node is that the local scratch should not be used (as it's not
+shared between nodes) and MPI or other technique for parallel multinode
+run has to be used properly.
+
+### Submit the job array
+
+To submit the job array, use the qsub -J command. The 900 jobs of the
+[example above](capacity-computing.html#array_example) may
+be submitted like this:
+
+`
+$ qsub -N JOBNAME -J 1-900 jobscript
+12345[].dm2
+`
+
+In this example, we submit a job array of 900 subjobs. Each subjob will
+run on full node and is assumed to take less than 2 hours (please note
+the #PBS directives in the beginning of the jobscript file, dont'
+forget to set your valid PROJECT_ID and desired queue).
+
+Sometimes for testing purposes, you may need to submit only one-element
+array. This is not allowed by PBSPro, but there's a workaround:
+
+`
+$ qsub -N JOBNAME -J 9-10:2 jobscript
+`
+
+This will only choose the lower index (9 in this example) for
+submitting/running your job.
+
+### Manage the job array
+
+Check status of the job array by the qstat command.
+
+`
+$ qstat -a 12345[].dm2
+
+dm2:
+ Req'd Req'd Elap
+Job ID Username Queue Jobname SessID NDS TSK Memory Time S Time
+--------------- -------- -- |---|---| ------ --- --- ------ ----- - -----
+12345[].dm2 user2 qprod xx 13516 1 16 -- 00:50 B 00:02
+`
+
+The status B means that some subjobs are already running.
+
+Check status of the first 100 subjobs by the qstat command.
+
+`
+$ qstat -a 12345[1-100].dm2
+
+dm2:
+ Req'd Req'd Elap
+Job ID Username Queue Jobname SessID NDS TSK Memory Time S Time
+--------------- -------- -- |---|---| ------ --- --- ------ ----- - -----
+12345[1].dm2 user2 qprod xx 13516 1 16 -- 00:50 R 00:02
+12345[2].dm2 user2 qprod xx 13516 1 16 -- 00:50 R 00:02
+12345[3].dm2 user2 qprod xx 13516 1 16 -- 00:50 R 00:01
+12345[4].dm2 user2 qprod xx 13516 1 16 -- 00:50 Q --
+ . . . . . . . . . . .
+ , . . . . . . . . . .
+12345[100].dm2 user2 qprod xx 13516 1 16 -- 00:50 Q --
+`
+
+Delete the entire job array. Running subjobs will be killed, queueing
+subjobs will be deleted.
+
+`
+$ qdel 12345[].dm2
+`
+
+Deleting large job arrays may take a while.
+
+Display status information for all user's jobs, job arrays, and subjobs.
+
+`
+$ qstat -u $USER -t
+`
+
+Display status information for all user's subjobs.
+
+`
+$ qstat -u $USER -tJ
+`
+
+Read more on job arrays in the [PBSPro Users
+guide](../../pbspro-documentation.html).
+
+GNU parallel
+----------------
+
+Use GNU parallel to run many single core tasks on one node.
+
+GNU parallel is a shell tool for executing jobs in parallel using one or
+more computers. A job can be a single command or a small script that has
+to be run for each of the lines in the input. GNU parallel is most
+useful in running single core jobs via the queue system on Anselm.
+
+For more information and examples see the parallel man page:
+
+`
+$ module add parallel
+$ man parallel
+`
+
+### GNU parallel jobscript
+
+The GNU parallel shell executes multiple instances of the jobscript
+using all cores on the node. The instances execute different work,
+controlled by the $PARALLEL_SEQ variable.
+
+Example:
+
+Assume we have 101 input files with name beginning with "file" (e. g.
+file001, ..., file101). Assume we would like to use each of these input
+files with program executable myprog.x, each as a separate single core
+job. We call these single core jobs tasks.
+
+First, we create a tasklist file, listing all tasks - all input files in
+our example:
+
+`
+$ find . -name 'file*' > tasklist
+`
+
+Then we create jobscript:
+
+`
+#!/bin/bash
+#PBS -A PROJECT_ID
+#PBS -q qprod
+#PBS -l select=1:ncpus=16,walltime=02:00:00
+
+[ -z "$PARALLEL_SEQ" ] &&
+{ module add parallel ; exec parallel -a $PBS_O_WORKDIR/tasklist $0 ; }
+
+# change to local scratch directory
+SCR=/lscratch/$PBS_JOBID/$PARALLEL_SEQ
+mkdir -p $SCR ; cd $SCR || exit
+
+# get individual task from tasklist
+TASK=$1 Â
+
+# copy input file and executable to scratch
+cp $PBS_O_WORKDIR/$TASK input
+
+# execute the calculation
+cat input > output
+
+# copy output file to submit directory
+cp output $PBS_O_WORKDIR/$TASK.out
+`
+
+In this example, tasks from tasklist are executed via the GNU
+parallel. The jobscript executes multiple instances of itself in
+parallel, on all cores of the node. Once an instace of jobscript is
+finished, new instance starts until all entries in tasklist are
+processed. Currently processed entry of the joblist may be retrieved via
+$1 variable. Variable $TASK expands to one of the input filenames from
+tasklist. We copy the input file to local scratch, execute the myprog.x
+and copy the output file back to the submit directory, under the
+$TASK.out name.Â
+
+### Submit the job
+
+To submit the job, use the qsub command. The 101 tasks' job of the
+[example above](capacity-computing.html#gp_example) may be
+submitted like this:
+
+`
+$ qsub -N JOBNAME jobscript
+12345.dm2
+`
+
+In this example, we submit a job of 101 tasks. 16 input files will be
+processed in parallel. The 101 tasks on 16 cores are assumed to
+complete in less than 2 hours.
+
+Please note the #PBS directives in the beginning of the jobscript file,
+dont' forget to set your valid PROJECT_ID and desired queue.
+
+Job arrays and GNU parallel
+-------------------------------
+
+Combine the Job arrays and GNU parallel for best throughput of single
+core jobs
+
+While job arrays are able to utilize all available computational nodes,
+the GNU parallel can be used to efficiently run multiple single-core
+jobs on single node. The two approaches may be combined to utilize all
+available (current and future) resources to execute single core jobs.
+
+Every subjob in an array runs GNU parallel to utilize all cores on the
+node
+
+### GNU parallel, shared jobscript
+
+Combined approach, very similar to job arrays, can be taken. Job array
+is submitted to the queuing system. The subjobs run GNU parallel. The
+GNU parallel shell executes multiple instances of the jobscript using
+all cores on the node. The instances execute different work, controlled
+by the $PBS_JOB_ARRAY and $PARALLEL_SEQ variables.
+
+Example:
+
+Assume we have 992 input files with name beginning with "file" (e. g.
+file001, ..., file992). Assume we would like to use each of these input
+files with program executable myprog.x, each as a separate single core
+job. We call these single core jobs tasks.
+
+First, we create a tasklist file, listing all tasks - all input files in
+our example:
+
+`
+$ find . -name 'file*' > tasklist
+`
+
+Next we create a file, controlling how many tasks will be executed in
+one subjob
+
+`
+$ seq 32 > numtasks
+`
+
+Then we create jobscript:
+
+`
+#!/bin/bash
+#PBS -A PROJECT_ID
+#PBS -q qprod
+#PBS -l select=1:ncpus=16,walltime=02:00:00
+
+[ -z "$PARALLEL_SEQ" ] &&
+{ module add parallel ; exec parallel -a $PBS_O_WORKDIR/numtasks $0 ; }
+
+# change to local scratch directory
+SCR=/lscratch/$PBS_JOBID/$PARALLEL_SEQ
+mkdir -p $SCR ; cd $SCR || exit
+
+# get individual task from tasklist with index from PBS JOB ARRAY and index form Parallel
+IDX=$(($PBS_ARRAY_INDEX + $PARALLEL_SEQ - 1))
+TASK=$(sed -n "${IDX}p" $PBS_O_WORKDIR/tasklist)
+[ -z "$TASK" ] && exit
+
+# copy input file and executable to scratch
+cp $PBS_O_WORKDIR/$TASK input
+
+# execute the calculation
+cat input > output
+
+# copy output file to submit directory
+cp output $PBS_O_WORKDIR/$TASK.out
+`
+
+In this example, the jobscript executes in multiple instances in
+parallel, on all cores of a computing node. Variable $TASK expands to
+one of the input filenames from tasklist. We copy the input file to
+local scratch, execute the myprog.x and copy the output file back to the
+submit directory, under the $TASK.out name. The numtasks file controls
+how many tasks will be run per subjob. Once an task is finished, new
+task starts, until the number of tasks in numtasks file is reached.
+
+Select subjob walltime and number of tasks per subjob carefully
+
+Â When deciding this values, think about following guiding rules :
+
+1. Let n=N/16. Inequality (n+1) * T < W should hold. The N is
+ number of tasks per subjob, T is expected single task walltime and W
+ is subjob walltime. Short subjob walltime improves scheduling and
+ job throughput.
+2. Number of tasks should be modulo 16.
+3. These rules are valid only when all tasks have similar task
+ walltimes T.
+
+### Submit the job array
+
+To submit the job array, use the qsub -J command. The 992 tasks' job of
+the [example
+above](capacity-computing.html#combined_example) may be
+submitted like this:
+
+`
+$ qsub -N JOBNAME -J 1-992:32 jobscript
+12345[].dm2
+`
+
+In this example, we submit a job array of 31 subjobs. Note the -J
+1-992:**32**, this must be the same as the number sent to numtasks file.
+Each subjob will run on full node and process 16 input files in
+parallel, 32 in total per subjob. Every subjob is assumed to complete
+in less than 2 hours.
+
+Please note the #PBS directives in the beginning of the jobscript file,
+dont' forget to set your valid PROJECT_ID and desired queue.
+
+Examples
+--------
+
+Download the examples in
+[capacity.zip](capacity-computing-examples),Â
+illustrating the above listed ways to run huge number of jobs. We
+recommend to try out the examples, before using this for running
+production jobs.
+
+Unzip the archive in an empty directory on Anselm and follow the
+instructions in the README file
+
+`
+$ unzip capacity.zip
+$ cat README
+`
+
+Â
+
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diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/resource-allocation-and-job-execution/introduction.md b/converted/docs.it4i.cz/anselm-cluster-documentation/resource-allocation-and-job-execution/introduction.md
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+Resource Allocation and Job Execution
+=====================================
+
+
+
+To run a [job](../introduction.html), [computational
+resources](../introduction.html) for this particular job
+must be allocated. This is done via the PBS Pro job workload manager
+software, which efficiently distributes workloads across the
+supercomputer. Extensive informations about PBS Pro can be found in the
+[official documentation
+here](../../pbspro-documentation.html), especially in
+the [PBS Pro User's
+Guide](https://docs.it4i.cz/pbspro-documentation/pbspro-users-guide).
+
+Resources Allocation Policy
+---------------------------
+
+The resources are allocated to the job in a fairshare fashion, subject
+to constraints set by the queue and resources available to the Project.
+[The Fairshare](job-priority.html) at Anselm ensures
+that individual users may consume approximately equal amount of
+resources per week. The resources are accessible via several queues for
+queueing the jobs. The queues provide prioritized and exclusive access
+to the computational resources. Following queues are available to Anselm
+users:
+
+- **qexp**, the \
+- **qprod**, the \***
+- **qlong**, the Long queue, regula
+- **qnvidia, qmic, qfat**, the Dedicated queues
+- **qfree,** the Free resource utilization queue
+
+Check the queue status at <https://extranet.it4i.cz/anselm/>
+
+Read more on the [Resource Allocation
+Policy](resources-allocation-policy.html) page.
+
+Job submission and execution
+----------------------------
+
+Use the **qsub** command to submit your jobs.
+
+The qsub submits the job into the queue. The qsub command creates a
+request to the PBS Job manager for allocation of specified resources.Â
+The **smallest allocation unit is entire node, 16 cores**, with
+exception of the qexp queue. The resources will be allocated when
+available, subject to allocation policies and constraints. **After the
+resources are allocated the jobscript or interactive shell is executed
+on first of the allocated nodes.**
+
+Read more on the [Job submission and
+execution](job-submission-and-execution.html) page.
+
+Capacity computing
+------------------
+
+Use Job arrays when running huge number of jobs.
+Use GNU Parallel and/or Job arrays when running (many) single core jobs.
+
+In many cases, it is useful to submit huge (>100+) number of
+computational jobs into the PBS queue system. Huge number of (small)
+jobs is one of the most effective ways to execute embarrassingly
+parallel calculations, achieving best runtime, throughput and computer
+utilization. In this chapter, we discuss the the recommended way to run
+huge number of jobs, including **ways to run huge number of single core
+jobs**.
+
+Read more on [Capacity
+computing](capacity-computing.html) page.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/resource-allocation-and-job-execution/job-priority.md b/converted/docs.it4i.cz/anselm-cluster-documentation/resource-allocation-and-job-execution/job-priority.md
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@@ -0,0 +1,103 @@
+Job scheduling
+==============
+
+Job execution priority
+----------------------
+
+Scheduler gives each job an execution priority and then uses this job
+execution priority to select which job(s) to run.
+
+Job execution priority on Anselm is determined by these job properties
+(in order of importance):
+
+1. queue priority
+2. fairshare priority
+3. eligible time
+
+### Queue priority
+
+Queue priority is priority of queue where job is queued before
+execution.
+
+Queue priority has the biggest impact on job execution priority.
+Execution priority of jobs in higher priority queues is always greater
+than execution priority of jobs in lower priority queues. Other
+properties of job used for determining job execution priority (fairshare
+priority, eligible time) cannot compete with queue priority.
+
+Queue priorities can be seen at <https://extranet.it4i.cz/anselm/queues>
+
+### Fairshare priority
+
+Fairshare priority is priority calculated on recent usage of resources.
+Fairshare priority is calculated per project, all members of project
+share same fairshare priority. Projects with higher recent usage have
+lower fairshare priority than projects with lower or none recent usage.
+
+Fairshare priority is used for ranking jobs with equal queue priority.
+
+Fairshare priority is calculated as
+
+
+
+where MAX_FAIRSHARE has value 1E6,
+usage~Project~ is cumulated usage by all members of selected project,
+usage~Total~ is total usage by all users, by all projects.
+
+Usage counts allocated corehours (ncpus*walltime). Usage is decayed, or
+cut in half periodically, at the interval 168 hours (one week).
+Jobs queued in queue qexp are not calculated to project's usage.
+
+Calculated usage and fairshare priority can be seen at
+<https://extranet.it4i.cz/anselm/projects>.
+
+Calculated fairshare priority can be also seen as
+Resource_List.fairshare attribute of a job.
+
+###Eligible time
+
+Eligible time is amount (in seconds) of eligible time job accrued while
+waiting to run. Jobs with higher eligible time gains higher
+priority.
+
+Eligible time has the least impact on execution priority. Eligible time
+is used for sorting jobs with equal queue priority and fairshare
+priority. It is very, very difficult for >eligible time to
+compete with fairshare priority.
+
+Eligible time can be seen as eligible_time attribute of
+job.
+
+### Formula
+
+Job execution priority (job sort formula) is calculated as:
+
+
+
+### Job backfilling
+
+Anselm cluster uses job backfilling.
+
+Backfilling means fitting smaller jobs around the higher-priority jobs
+that the scheduler is going to run next, in such a way that the
+higher-priority jobs are not delayed. Backfilling allows us to keep
+resources from becoming idle when the top job (job with the highest
+execution priority) cannot run.
+
+The scheduler makes a list of jobs to run in order of execution
+priority. Scheduler looks for smaller jobs that can fit into the usage
+gaps
+around the highest-priority jobs in the list. The scheduler looks in the
+prioritized list of jobs and chooses the highest-priority smaller jobs
+that fit. Filler jobs are run only if they will not delay the start time
+of top jobs.
+
+It means, that jobs with lower execution priority can be run before jobs
+with higher execution priority.
+
+It is **very beneficial to specify the walltime** when submitting jobs.
+
+Specifying more accurate walltime enables better schedulling, better
+execution times and better resource usage. Jobs with suitable (small)
+walltime could be backfilled - and overtake job(s) with higher priority.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/resource-allocation-and-job-execution/job-submission-and-execution.md b/converted/docs.it4i.cz/anselm-cluster-documentation/resource-allocation-and-job-execution/job-submission-and-execution.md
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+Job submission and execution
+============================
+
+
+
+Job Submission
+--------------
+
+When allocating computational resources for the job, please specify
+
+1. suitable queue for your job (default is qprod)
+2. number of computational nodes required
+3. number of cores per node required
+4. maximum wall time allocated to your calculation, note that jobs
+ exceeding maximum wall time will be killed
+5. Project ID
+6. Jobscript or interactive switch
+
+Use the **qsub** command to submit your job to a queue for allocation of
+the computational resources.
+
+Submit the job using the qsub command:
+
+`
+$ qsub -A Project_ID -q queue -l select=x:ncpus=y,walltime=[[hh:]mm:]ss[.ms] jobscript
+`
+
+The qsub submits the job into the queue, in another words the qsub
+command creates a request to the PBS Job manager for allocation of
+specified resources. The resources will be allocated when available,
+subject to above described policies and constraints. **After the
+resources are allocated the jobscript or interactive shell is executed
+on first of the allocated nodes.**
+
+### Job Submission Examples
+
+`
+$ qsub -A OPEN-0-0 -q qprod -l select=64:ncpus=16,walltime=03:00:00 ./myjob
+`
+
+In this example, we allocate 64 nodes, 16 cores per node, for 3 hours.
+We allocate these resources via the qprod queue, consumed resources will
+be accounted to the Project identified by Project ID OPEN-0-0. Jobscript
+myjob will be executed on the first node in the allocation.
+
+Â
+
+`
+$ qsub -q qexp -l select=4:ncpus=16 -I
+`
+
+In this example, we allocate 4 nodes, 16 cores per node, for 1 hour. We
+allocate these resources via the qexp queue. The resources will be
+available interactively
+
+Â
+
+`
+$ qsub -A OPEN-0-0 -q qnvidia -l select=10:ncpus=16 ./myjob
+`
+
+In this example, we allocate 10 nvidia accelerated nodes, 16 cores per
+node, for 24 hours. We allocate these resources via the qnvidia queue.
+Jobscript myjob will be executed on the first node in the allocation.
+
+Â
+
+`
+$ qsub -A OPEN-0-0 -q qfree -l select=10:ncpus=16 ./myjob
+`
+
+In this example, we allocate 10Â nodes, 16 cores per node, for 12 hours.
+We allocate these resources via the qfree queue. It is not required that
+the project OPEN-0-0 has any available resources left. Consumed
+resources are still accounted for. Jobscript myjob will be executed on
+the first node in the allocation.
+
+Â
+
+All qsub options may be [saved directly into the
+jobscript](job-submission-and-execution.html#PBSsaved). In
+such a case, no options to qsub are needed.
+
+`
+$ qsub ./myjob
+`
+
+Â
+
+By default, the PBS batch system sends an e-mail only when the job is
+aborted. Disabling mail events completely can be done like this:
+
+`
+$ qsub -m n
+`
+
+Advanced job placement
+----------------------
+
+### Placement by name
+
+Specific nodes may be allocated via the PBS
+
+`
+qsub -A OPEN-0-0 -q qprod -l select=1:ncpus=16:host=cn171+1:ncpus=16:host=cn172 -I
+`
+
+In this example, we allocate nodes cn171 and cn172, all 16 cores per
+node, for 24 hours. Consumed resources will be accounted to the Project
+identified by Project ID OPEN-0-0. The resources will be available
+interactively.
+
+### Placement by CPU type
+
+Nodes equipped with Intel Xeon E5-2665 CPU have base clock frequency
+2.4GHz, nodes equipped with Intel Xeon E5-2470 CPU have base frequency
+2.3 GHz (see section Compute Nodes for details). Nodes may be selected
+via the PBS resource attribute
+cpu_freq .
+
+ CPU Type base freq. Nodes cpu_freq attribute
+ -------------- |---|---|-- ---------------------------- ---------------------
+ Intel Xeon E5-2665 2.4GHz cn[1-180], cn[208-209] 24
+ Intel Xeon E5-2470 2.3GHz cn[181-207] 23
+
+Â
+
+`
+$ qsub -A OPEN-0-0 -q qprod -l select=4:ncpus=16:cpu_freq=24 -I
+`
+
+In this example, we allocate 4 nodes, 16 cores, selecting only the nodes
+with Intel Xeon E5-2665 CPU.
+
+### Placement by IB switch
+
+Groups of computational nodes are connected to chassis integrated
+Infiniband switches. These switches form the leaf switch layer of the
+[Infiniband network](../network.html)
+fat tree topology. Nodes sharing the leaf
+switch can communicate most efficiently. Sharing the same switch
+prevents hops in the network and provides for unbiased, most efficient
+network communication.
+
+Nodes sharing the same switch may be selected via the PBS resource
+attribute ibswitch. Values of this attribute are iswXX, where XX is the
+switch number. The node-switch mapping can be seen at [Hardware
+Overview](../hardware-overview.html) section.
+
+We recommend allocating compute nodes of a single switch when best
+possible computational network performance is required to run the job
+efficiently:
+
+ qsub -A OPEN-0-0 -q qprod -l select=18:ncpus=16:ibswitch=isw11 ./myjob
+
+In this example, we request all the 18 nodes sharing the isw11 switch
+for 24 hours. Full chassis will be allocated.
+
+Advanced job handling
+---------------------
+
+### Selecting Turbo Boost off
+
+Intel Turbo Boost Technology is on by default. We strongly recommend
+keeping the default.Â
+
+If necessary (such as in case of benchmarking) you can disable the Turbo
+for all nodes of the job by using the PBS resource attribute
+cpu_turbo_boost
+
+ $ qsub -A OPEN-0-0 -q qprod -l select=4:ncpus=16 -l cpu_turbo_boost=0 -I
+
+More about the Intel Turbo Boost in the TurboBoost section
+
+### Advanced examples
+
+In the following example, we select an allocation for benchmarking a
+very special and demanding MPI program. We request Turbo off, 2 full
+chassis of compute nodes (nodes sharing the same IB switches) for 30
+minutes:
+
+ $ qsub -A OPEN-0-0 -q qprod
+ -l select=18:ncpus=16:ibswitch=isw10:mpiprocs=1:ompthreads=16+18:ncpus=16:ibswitch=isw20:mpiprocs=16:ompthreads=1
+ -l cpu_turbo_boost=0,walltime=00:30:00
+ -N Benchmark ./mybenchmark
+
+The MPI processes will be distributed differently on the nodes connected
+to the two switches. On the isw10 nodes, we will run 1 MPI process per
+node 16 threads per process, on isw20Â nodes we will run 16 plain MPI
+processes.
+
+Although this example is somewhat artificial, it demonstrates the
+flexibility of the qsub command options.
+
+Job Management
+--------------
+
+Check status of your jobs using the **qstat** and **check-pbs-jobs**
+commands
+
+`
+$ qstat -a
+$ qstat -a -u username
+$ qstat -an -u username
+$ qstat -f 12345.srv11
+`
+
+Example:
+
+`
+$ qstat -a
+
+srv11:
+ Req'd Req'd Elap
+Job ID Username Queue Jobname SessID NDS TSK Memory Time S Time
+--------------- -------- -- |---|---| ------ --- --- ------ ----- - -----
+16287.srv11 user1 qlong job1 6183 4 64 -- 144:0 R 38:25
+16468.srv11 user1 qlong job2 8060 4 64 -- 144:0 R 17:44
+16547.srv11 user2 qprod job3x 13516 2 32 -- 48:00 R 00:58
+`
+
+In this example user1 and user2 are running jobs named job1, job2 and
+job3x. The jobs job1 and job2 are using 4 nodes, 16 cores per node each.
+The job1 already runs for 38 hours and 25 minutes, job2 for 17 hours 44
+minutes. The job1 already consumed 64*38.41 = 2458.6 core hours. The
+job3x already consumed 0.96*32 = 30.93 core hours. These consumed core
+hours will be accounted on the respective project accounts, regardless
+of whether the allocated cores were actually used for computations.
+
+Check status of your jobs using check-pbs-jobs command. Check presence
+of user's PBS jobs' processes on execution hosts. Display load,
+processes. Display job standard and error output. Continuously display
+(tail -f) job standard or error output.
+
+`
+$ check-pbs-jobs --check-all
+$ check-pbs-jobs --print-load --print-processes
+$ check-pbs-jobs --print-job-out --print-job-err
+
+$ check-pbs-jobs --jobid JOBID --check-all --print-all
+
+$ check-pbs-jobs --jobid JOBID --tailf-job-out
+`
+
+Examples:
+
+`
+$ check-pbs-jobs --check-all
+JOB 35141.dm2, session_id 71995, user user2, nodes cn164,cn165
+Check session id: OK
+Check processes
+cn164: OK
+cn165: No process
+`
+
+In this example we see that job 35141.dm2 currently runs no process on
+allocated node cn165, which may indicate an execution error.
+
+`
+$ check-pbs-jobs --print-load --print-processes
+JOB 35141.dm2, session_id 71995, user user2, nodes cn164,cn165
+Print load
+cn164: LOAD: 16.01, 16.01, 16.00
+cn165: LOAD: 0.01, 0.00, 0.01
+Print processes
+ %CPU CMD
+cn164: 0.0 -bash
+cn164: 0.0 /bin/bash /var/spool/PBS/mom_priv/jobs/35141.dm2.SC
+cn164: 99.7 run-task
+...
+`
+
+In this example we see that job 35141.dm2 currently runs process
+run-task on node cn164, using one thread only, while node cn165 is
+empty, which may indicate an execution error.
+
+`
+$ check-pbs-jobs --jobid 35141.dm2 --print-job-out
+JOB 35141.dm2, session_id 71995, user user2, nodes cn164,cn165
+Print job standard output:
+======================== Job start ==========================
+Started at   : Fri Aug 30 02:47:53 CEST 2013
+Script name  : script
+Run loop 1
+Run loop 2
+Run loop 3
+`
+
+In this example, we see actual output (some iteration loops) of the job
+35141.dm2
+
+Manage your queued or running jobs, using the **qhold**, **qrls**,
+qdel,** **qsig** or **qalter** commands
+
+You may release your allocation at any time, using qdel command
+
+`
+$ qdel 12345.srv11
+`
+
+You may kill a running job by force, using qsig command
+
+`
+$ qsig -s 9 12345.srv11
+`
+
+Learn more by reading the pbs man page
+
+`
+$ man pbs_professional
+`
+
+Job Execution
+-------------
+
+### Jobscript
+
+Prepare the jobscript to run batch jobs in the PBS queue system
+
+The Jobscript is a user made script, controlling sequence of commands
+for executing the calculation. It is often written in bash, other
+scripts may be used as well. The jobscript is supplied to PBS **qsub**
+command as an argument and executed by the PBS Professional workload
+manager.
+
+The jobscript or interactive shell is executed on first of the allocated
+nodes.
+
+`
+$ qsub -q qexp -l select=4:ncpus=16 -N Name0 ./myjob
+$ qstat -n -u username
+
+srv11:
+ Req'd Req'd Elap
+Job ID Username Queue Jobname SessID NDS TSK Memory Time S Time
+--------------- -------- -- |---|---| ------ --- --- ------ ----- - -----
+15209.srv11 username qexp Name0 5530 4 64 -- 01:00 R 00:00
+ cn17/0*16+cn108/0*16+cn109/0*16+cn110/0*16
+`
+
+Â In this example, the nodes cn17, cn108, cn109 and cn110 were allocated
+for 1 hour via the qexp queue. The jobscript myjob will be executed on
+the node cn17, while the nodes cn108, cn109 and cn110 are available for
+use as well.
+
+The jobscript or interactive shell is by default executed in home
+directory
+
+`
+$ qsub -q qexp -l select=4:ncpus=16 -I
+qsub: waiting for job 15210.srv11 to start
+qsub: job 15210.srv11 ready
+
+$ pwd
+/home/username
+`
+
+In this example, 4 nodes were allocated interactively for 1 hour via the
+qexp queue. The interactive shell is executed in the home directory.
+
+All nodes within the allocation may be accessed via ssh. Unallocated
+nodes are not accessible to user.
+
+The allocated nodes are accessible via ssh from login nodes. The nodes
+may access each other via ssh as well.
+
+Calculations on allocated nodes may be executed remotely via the MPI,
+ssh, pdsh or clush. You may find out which nodes belong to the
+allocation by reading the $PBS_NODEFILE file
+
+`
+qsub -q qexp -l select=4:ncpus=16 -I
+qsub: waiting for job 15210.srv11 to start
+qsub: job 15210.srv11 ready
+
+$ pwd
+/home/username
+
+$ sort -u $PBS_NODEFILE
+cn17.bullx
+cn108.bullx
+cn109.bullx
+cn110.bullx
+
+$ pdsh -w cn17,cn[108-110] hostname
+cn17: cn17
+cn108: cn108
+cn109: cn109
+cn110: cn110
+`
+
+In this example, the hostname program is executed via pdsh from the
+interactive shell. The execution runs on all four allocated nodes. The
+same result would be achieved if the pdsh is called from any of the
+allocated nodes or from the login nodes.
+
+### Example Jobscript for MPI Calculation
+
+Production jobs must use the /scratch directory for I/O
+
+The recommended way to run production jobs is to change to /scratch
+directory early in the jobscript, copy all inputs to /scratch, execute
+the calculations and copy outputs to home directory.
+
+`
+#!/bin/bash
+
+# change to scratch directory, exit on failure
+SCRDIR=/scratch/$USER/myjob
+mkdir -p $SCRDIR
+cd $SCRDIR || exit
+
+# copy input file to scratch
+cp $PBS_O_WORKDIR/input .
+cp $PBS_O_WORKDIR/mympiprog.x .
+
+# load the mpi module
+module load openmpi
+
+# execute the calculation
+mpiexec -pernode ./mympiprog.x
+
+# copy output file to home
+cp output $PBS_O_WORKDIR/.
+
+#exit
+exit
+`
+
+In this example, some directory on the /home holds the input file input
+and executable mympiprog.x . We create a directory myjob on the /scratch
+filesystem, copy input and executable files from the /home directory
+where the qsub was invoked ($PBS_O_WORKDIR) to /scratch, execute the
+MPI programm mympiprog.x and copy the output file back to the /home
+directory. The mympiprog.x is executed as one process per node, on all
+allocated nodes.
+
+Consider preloading inputs and executables onto [shared
+scratch](../storage.html) before the calculation starts.
+
+In some cases, it may be impractical to copy the inputs to scratch and
+outputs to home. This is especially true when very large input and
+output files are expected, or when the files should be reused by a
+subsequent calculation. In such a case, it is users responsibility to
+preload the input files on shared /scratch before the job submission and
+retrieve the outputs manually, after all calculations are finished.
+
+Store the qsub options within the jobscript.
+Use **mpiprocs** and **ompthreads** qsub options to control the MPI job
+execution.
+
+Example jobscript for an MPI job with preloaded inputs and executables,
+options for qsub are stored within the script :
+
+`
+#!/bin/bash
+#PBS -q qprod
+#PBS -N MYJOB
+#PBS -l select=100:ncpus=16:mpiprocs=1:ompthreads=16
+#PBS -A OPEN-0-0
+
+# change to scratch directory, exit on failure
+SCRDIR=/scratch/$USER/myjob
+cd $SCRDIR || exit
+
+# load the mpi module
+module load openmpi
+
+# execute the calculation
+mpiexec ./mympiprog.x
+
+#exit
+exit
+`
+
+In this example, input and executable files are assumed preloaded
+manually in /scratch/$USER/myjob directory. Note the **mpiprocs** and
+ompthreads** qsub options, controlling behavior of the MPI execution.
+The mympiprog.x is executed as one process per node, on all 100
+allocated nodes. If mympiprog.x implements OpenMP threads, it will run
+16 threads per node.
+
+More information is found in the [Running
+OpenMPI](../software/mpi-1/Running_OpenMPI.html) and
+[Running MPICH2](../software/mpi-1/running-mpich2.html)
+sections.
+
+### Example Jobscript for Single Node Calculation
+
+Local scratch directory is often useful for single node jobs. Local
+scratch will be deleted immediately after the job ends.
+
+Example jobscript for single node calculation, using [local
+scratch](../storage.html) on the node:
+
+`
+#!/bin/bash
+
+# change to local scratch directory
+cd /lscratch/$PBS_JOBID || exit
+
+# copy input file to scratch
+cp $PBS_O_WORKDIR/input .
+cp $PBS_O_WORKDIR/myprog.x .
+
+# execute the calculation
+./myprog.x
+
+# copy output file to home
+cp output $PBS_O_WORKDIR/.
+
+#exit
+exit
+`
+
+In this example, some directory on the home holds the input file input
+and executable myprog.x . We copy input and executable files from the
+home directory where the qsub was invoked ($PBS_O_WORKDIR) to local
+scratch /lscratch/$PBS_JOBID, execute the myprog.x and copy the output
+file back to the /home directory. The myprog.x runs on one node only and
+may use threads.
+
+### Other Jobscript Examples
+
+Further jobscript examples may be found in the
+[Software](../software.1.html) section and the [Capacity
+computing](capacity-computing.html) section.
+
+Â
+
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@@ -0,0 +1,213 @@
+Resources Allocation Policy
+===========================
+
+
+
+Resources Allocation Policy
+---------------------------
+
+The resources are allocated to the job in a fairshare fashion, subject
+to constraints set by the queue and resources available to the Project.
+The Fairshare at Anselm ensures that individual users may consume
+approximately equal amount of resources per week. Detailed information
+in the [Job scheduling](job-priority.html) section. The
+resources are accessible via several queues for queueing the jobs. The
+queues provide prioritized and exclusive access to the computational
+resources. Following table provides the queue partitioning overview:Â Â
+Â
+
+ |queue |active project |project resources |nodes<th align="left">min ncpus*<th align="left">priority<th align="left">authorization<th align="left">walltime |
+ | --- | --- |
+ |<strong>qexp</strong>\ |no |none required |2 reserved, 31 totalincluding MIC, GPU and FAT nodes |1 |><em>150</em> |no |1h |
+ |<strong>qprod</strong>\ |yes |> 0 |><em>178 nodes w/o accelerator</em>\ |16 |0 |no |24/48h |
+ |<strong>qlong</strong>Long queue\ |yes |> 0 |60 nodes w/o accelerator |16 |0 |no |72/144h |
+ |<strong>qnvidia, qmic, qfat</strong>Dedicated queues\ |yes |<p>> 0\ |23 total qnvidia4 total qmic2 total qfat |16 |><em>200</em> |yes |24/48h |
+ |<strong>qfree</strong>\ |yes |none required |178 w/o accelerator |16 |-1024 |no |12h |
+
+The qfree queue is not free of charge**. [Normal
+accounting](resources-allocation-policy.html#resources-accounting-policy)
+applies. However, it allows for utilization of free resources, once a
+Project exhausted all its allocated computational resources. This does
+not apply for Directors Discreation's projects (DD projects) by default.
+Usage of qfree after exhaustion of DD projects computational resources
+is allowed after request for this queue.
+
+The qexp queue is equipped with the nodes not having the very same CPU
+clock speed.** Should you need the very same CPU speed, you have to
+select the proper nodes during the PSB job submission.
+**
+
+- **qexp**, the \: This queue is dedicated for testing and
+ running very small jobs. It is not required to specify a project to
+ enter the qexp. >*>There are 2 nodes always reserved for
+ this queue (w/o accelerator), maximum 8 nodes are available via the
+ qexp for a particular user, from a pool of nodes containing
+ **Nvidia** accelerated nodes (cn181-203), **MIC** accelerated
+ nodes (cn204-207) and **Fat** nodes with 512GB RAM (cn208-209). This
+ enables to test and tune also accelerated code or code with higher
+ RAM requirements.* The nodes may be allocated on per
+ core basis. No special authorization is required to use it. The
+ maximum runtime in qexp is 1 hour.
+- **qprod**, the \***: This queue is intended for
+ normal production runs. It is required that active project with
+ nonzero remaining resources is specified to enter the qprod. All
+ nodes may be accessed via the qprod queue, except the reserved ones.
+ >*>178 nodes without accelerator are
+ included.*Â Full nodes, 16 cores per node
+ are allocated. The queue runs with medium priority and no special
+ authorization is required to use it. The maximum runtime in qprod is
+ 48 hours.
+- **qlong**, the Long queue***: This queue is intended for long
+ production runs. It is required that active project with nonzero
+ remaining resources is specified to enter the qlong. Only 60 nodes
+ without acceleration may be accessed via the qlong queue. Full
+ nodes, 16 cores per node are allocated. The queue runs with medium
+ priority and no special authorization is required to use it.>
+ *The maximum runtime in qlong is 144 hours (three times of the
+ standard qprod time - 3 * 48 h).*
+- **qnvidia, qmic, qfat**, the Dedicated queues***: The queue qnvidia
+ is dedicated to access the Nvidia accelerated nodes, the qmic to
+ access MIC nodes and qfat the Fat nodes. It is required that active
+ project with nonzero remaining resources is specified to enter
+ these queues. 23 nvidia, 4 mic and 2 fat nodes are included. Full
+ nodes, 16 cores per node are allocated. The queues run with>
+ *very high priority*, the jobs will be scheduled before the
+ jobs coming from the> *qexp* queue. An PI> *needs
+ explicitly* ask
+ [support](https://support.it4i.cz/rt/) for
+ authorization to enter the dedicated queues for all users associated
+ to her/his Project.
+- **qfree**, The \***: The queue qfree is intended
+ for utilization of free resources, after a Project exhausted all its
+ allocated computational resources (Does not apply to DD projects
+ by default. DD projects have to request for persmission on qfree
+ after exhaustion of computational resources.). It is required that
+ active project is specified to enter the queue, however no remaining
+ resources are required. Consumed resources will be accounted to
+ the Project. Only 178 nodes without accelerator may be accessed from
+ this queue. Full nodes, 16 cores per node are allocated. The queue
+ runs with very low priority and no special authorization is required
+ to use it. The maximum runtime in qfree is 12 hours.
+
+### Notes
+
+The job wall clock time defaults to **half the maximum time**, see table
+above. Longer wall time limits can be [set manually, see
+examples](job-submission-and-execution.html).
+
+Jobs that exceed the reserved wall clock time (Req'd Time) get killed
+automatically. Wall clock time limit can be changed for queuing jobs
+(state Q) using the qalter command, however can not be changed for a
+running job (state R).
+
+Anselm users may check current queue configuration at
+<https://extranet.it4i.cz/anselm/queues>.
+
+### Queue status
+
+Check the status of jobs, queues and compute nodes at
+<https://extranet.it4i.cz/anselm/>
+
+
+
+Display the queue status on Anselm:
+
+`
+$ qstat -q
+`
+
+The PBS allocation overview may be obtained also using the rspbs
+command.
+
+`
+$ rspbs
+Usage: rspbs [options]
+
+Options:
+ --version            show program's version number and exit
+ -h, --help           show this help message and exit
+Â --get-node-ncpu-chart
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print chart of allocated ncpus per node
+ --summary            Print summary
+ --get-server-details Print server
+ --get-queues         Print queues
+ --get-queues-details Print queues details
+ --get-reservations   Print reservations
+Â --get-reservations-details
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print reservations details
+ --get-nodes          Print nodes of PBS complex
+ --get-nodeset        Print nodeset of PBS complex
+ --get-nodes-details  Print nodes details
+ --get-jobs           Print jobs
+ --get-jobs-details   Print jobs details
+Â --get-jobs-check-params
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print jobid, job state, session_id, user, nodes
+ --get-users          Print users of jobs
+Â --get-allocated-nodes
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print allocated nodes of jobs
+Â --get-allocated-nodeset
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print allocated nodeset of jobs
+ --get-node-users     Print node users
+ --get-node-jobs      Print node jobs
+ --get-node-ncpus     Print number of ncpus per node
+Â --get-node-allocated-ncpus
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print number of allocated ncpus per node
+ --get-node-qlist     Print node qlist
+ --get-node-ibswitch  Print node ibswitch
+ --get-user-nodes     Print user nodes
+ --get-user-nodeset   Print user nodeset
+ --get-user-jobs      Print user jobs
+ --get-user-jobc      Print number of jobs per user
+ --get-user-nodec     Print number of allocated nodes per user
+ --get-user-ncpus     Print number of allocated ncpus per user
+ --get-qlist-nodes    Print qlist nodes
+ --get-qlist-nodeset  Print qlist nodeset
+ --get-ibswitch-nodes Print ibswitch nodes
+Â --get-ibswitch-nodeset
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print ibswitch nodeset
+Â --state=STATEÂ Â Â Â Â Â Â Â Only for given job state
+Â --jobid=JOBIDÂ Â Â Â Â Â Â Â Only for given job ID
+Â --user=USERÂ Â Â Â Â Â Â Â Â Â Only for given user
+Â --node=NODEÂ Â Â Â Â Â Â Â Â Â Only for given node
+Â --nodestate=NODESTATE
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Only for given node state (affects only --get-node*
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â --get-qlist-* --get-ibswitch-* actions)
+ --incl-finished      Include finished jobs
+`
+
+Resources Accounting Policy
+-------------------------------
+
+### The Core-Hour
+
+The resources that are currently subject to accounting are the
+core-hours. The core-hours are accounted on the wall clock basis. The
+accounting runs whenever the computational cores are allocated or
+blocked via the PBS Pro workload manager (the qsub command), regardless
+of whether the cores are actually used for any calculation. 1 core-hour
+is defined as 1 processor core allocated for 1 hour of wall clock time.
+Allocating a full node (16 cores) for 1 hour accounts to 16 core-hours.
+See example in the [Job submission and
+execution](job-submission-and-execution.html) section.
+
+### Check consumed resources
+
+The **it4ifree** command is a part of it4i.portal.clients package,
+located here:
+<https://pypi.python.org/pypi/it4i.portal.clients>
+
+User may check at any time, how many core-hours have been consumed by
+himself/herself and his/her projects. The command is available on
+clusters' login nodes.
+
+`
+$ it4ifree
+Password:
+    PID  Total Used ...by me Free
+Â Â -------- ------- ------ -------- -------
+Â Â OPEN-0-0 1500000 400644Â Â 225265 1099356
+Â Â DD-13-1 Â Â 10000 2606 2606 7394
+`
+
+Â
+
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+Overview of ANSYS Products
+==========================
+
+[SVS FEM](http://www.svsfem.cz/)** as **[ANSYS
+Channel partner](http://www.ansys.com/)**Â for Czech
+Republic provided all ANSYS licenses for ANSELM cluster and supports of
+all ANSYS Products (Multiphysics, Mechanical, MAPDL, CFX, Fluent,
+Maxwell, LS-DYNA...) to IT staff and ANSYS users. If you are challenging
+to problem of ANSYS functionality contact
+please [hotline@svsfem.cz](mailto:hotline@svsfem.cz?subject=Ostrava%20-%20ANSELM)
+
+Anselm provides as commercial as academic variants. Academic variants
+are distinguished by "**Academic...**" word in the name of  license or
+by two letter preposition "**aa_**" in the license feature name. Change
+of license is realized on command line respectively directly in user's
+pbs file (see individual products). [
+ More about
+licensing
+here](ansys/licensing.html)
+
+To load the latest version of any ANSYS product (Mechanical, Fluent,
+CFX, MAPDL,...) load the module:
+
+ $ module load ansys
+
+ANSYS supports interactive regime, but due to assumed solution of
+extremely difficult tasks it is not recommended.
+
+If user needs to work in interactive regime we recommend to configure
+the RSM service on the client machine which allows to forward the
+solution to the Anselm directly from the client's Workbench project
+(see ANSYS RSM service).
+
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diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-cfx.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-cfx.md
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index 0000000000000000000000000000000000000000..5d50cda135ee04d574eb928dbb7b2aedf1a87013
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-cfx.md
@@ -0,0 +1,87 @@
+ANSYS CFX
+=========
+
+[ANSYS
+CFX](http://www.ansys.com/Products/Simulation+Technology/Fluid+Dynamics/Fluid+Dynamics+Products/ANSYS+CFX)
+software is a high-performance, general purpose fluid dynamics program
+that has been applied to solve wide-ranging fluid flow problems for over
+20 years. At the heart of ANSYS CFX is its advanced solver technology,
+the key to achieving reliable and accurate solutions quickly and
+robustly. The modern, highly parallelized solver is the foundation for
+an abundant choice of physical models to capture virtually any type of
+phenomena related to fluid flow. The solver and its many physical models
+are wrapped in a modern, intuitive, and flexible GUI and user
+environment, with extensive capabilities for customization and
+automation using session files, scripting and a powerful expression
+language.
+
+To run ANSYS CFX in batch mode you can utilize/modify the default
+cfx.pbs script and execute it via the qsub command.
+
+`
+#!/bin/bash
+#PBS -l nodes=2:ppn=16
+#PBS -q qprod
+#PBS -N $USER-CFX-Project
+#PBS -A XX-YY-ZZ
+
+#! Mail to user when job terminate or abort
+#PBS -m ae
+
+#!change the working directory (default is home directory)
+#cd <working directory> (working directory must exists)
+WORK_DIR="/scratch/$USER/work"
+cd $WORK_DIR
+
+echo Running on host `hostname`
+echo Time is `date`
+echo Directory is `pwd`
+echo This jobs runs on the following processors:
+echo `cat $PBS_NODEFILE`
+
+module load ansys
+
+#### Set number of processors per host listing
+#### (set to 1 as $PBS_NODEFILE lists each node twice if :ppn=2)
+procs_per_host=1
+#### Create host list
+hl=""
+for host in `cat $PBS_NODEFILE`
+do
+ if [ "$hl" = "" ]
+ then hl="$host:$procs_per_host"
+ else hl="${hl}:$host:$procs_per_host"
+ fi
+done
+
+echo Machines: $hl
+
+#-dev input.def includes the input of CFX analysis in DEF format
+#-P the name of prefered license feature (aa_r=ANSYS Academic Research, ane3fl=Multiphysics(commercial))
+/ansys_inc/v145/CFX/bin/cfx5solve -def input.def -size 4 -size-ni 4x -part-large -start-method "Platform MPI Distributed Parallel" -par-dist $hl -P aa_r
+`
+
+Header of the pbs file (above) is common and description can be find
+on [this
+site](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+SVS FEM recommends to utilize sources by keywords: nodes, ppn. These
+keywords allows to address directly the number of nodes (computers) and
+cores (ppn) which will be utilized in the job. Also the rest of code
+assumes such structure of allocated resources.
+
+Working directory has to be created before sending pbs job into the
+queue. Input file should be in working directory or full path to input
+file has to be specified. >Input file has to be defined by common
+CFX def file which is attached to the cfx solver via parameter
+-def
+
+License**Â should be selected by parameter -P (Big letter **P**).
+Licensed products are the following: aa_r
+(ANSYS **Academic Research), ane3fl (ANSYS
+Multiphysics)-**Commercial.
+[ More
+ about licensing
+here](licensing.html)
+
+Â
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-fluent.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-fluent.md
new file mode 100644
index 0000000000000000000000000000000000000000..ab675d3381dc6377e63df7b7a5db21ff7db72aff
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-fluent.md
@@ -0,0 +1,228 @@
+ANSYS Fluent
+============
+
+[ANSYS
+Fluent](http://www.ansys.com/Products/Simulation+Technology/Fluid+Dynamics/Fluid+Dynamics+Products/ANSYS+Fluent)
+software contains the broad physical modeling capabilities needed to
+model flow, turbulence, heat transfer, and reactions for industrial
+applications ranging from air flow over an aircraft wing to combustion
+in a furnace, from bubble columns to oil platforms, from blood flow to
+semiconductor manufacturing, and from clean room design to wastewater
+treatment plants. Special models that give the software the ability to
+model in-cylinder combustion, aeroacoustics, turbomachinery, and
+multiphase systems have served to broaden its reach.
+
+1. Common way to run Fluent over pbs file
+------------------------------------------------------
+
+To run ANSYS Fluent in batch mode you can utilize/modify the
+default fluent.pbs script and execute it via the qsub command.
+
+`
+#!/bin/bash
+#PBS -S /bin/bash
+#PBS -l nodes=2:ppn=16
+#PBS -q qprod
+#PBS -N $USER-Fluent-Project
+#PBS -A XX-YY-ZZ
+
+#! Mail to user when job terminate or abort
+#PBS -m ae
+
+#!change the working directory (default is home directory)
+#cd <working directory> (working directory must exists)
+WORK_DIR="/scratch/$USER/work"
+cd $WORK_DIR
+
+echo Running on host `hostname`
+echo Time is `date`
+echo Directory is `pwd`
+echo This jobs runs on the following processors:
+echo `cat $PBS_NODEFILE`
+
+#### Load ansys module so that we find the cfx5solve command
+module load ansys
+
+# Use following line to specify MPI for message-passing instead
+NCORES=`wc -l $PBS_NODEFILE |awk '{print $1}'`
+
+/ansys_inc/v145/fluent/bin/fluent 3d -t$NCORES -cnf=$PBS_NODEFILE -g -i fluent.jou
+`
+
+Header of the pbs file (above) is common and description can be find
+on [this
+site](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+[SVS FEM](http://www.svsfem.cz) recommends to utilize
+sources by keywords: nodes, ppn. These keywords allows to address
+directly the number of nodes (computers) and cores (ppn) which will be
+utilized in the job. Also the rest of code assumes such structure of
+allocated resources.
+
+Working directory has to be created before sending pbs job into the
+queue. Input file should be in working directory or full path to input
+file has to be specified. Input file has to be defined by common Fluent
+journal file which is attached to the Fluent solver via parameter -i
+fluent.jou
+
+Journal file with definition of the input geometry and boundary
+conditions and defined process of solution has e.g. the following
+structure:
+
+ /file/read-case aircraft_2m.cas.gz
+ /solve/init
+ init
+ /solve/iterate
+ 10
+ /file/write-case-dat aircraft_2m-solution
+ /exit yes
+
+The appropriate dimension of the problem has to be set by
+parameter (2d/3d).Â
+
+2. Fast way to run Fluent from command line
+--------------------------------------------------------
+
+`
+fluent solver_version [FLUENT_options] -i journal_file -pbs
+`
+
+This syntax will start the ANSYS FLUENT job under PBS Professional using
+the qsub command in a batch manner. When
+resources are available, PBS Professional will start the job and return
+a job ID, usually in the form of
+*job_ID.hostname*. This job ID can then be used
+to query, control, or stop the job using standard PBS Professional
+commands, such as qstat or
+qdel. The job will be run out of the current
+working directory, and all output will be written to the file
+fluent.o>Â
+*job_ID*. Â Â Â Â
+
+3. Running Fluent via user's config file
+----------------------------------------
+
+The sample script uses a configuration file called
+pbs_fluent.conf  if no command line arguments
+are present. This configuration file should be present in the directory
+from which the jobs are submitted (which is also the directory in which
+the jobs are executed). The following is an example of what the content
+of pbs_fluent.conf can be:
+
+`
+input="example_small.flin"
+case="Small-1.65m.cas"
+fluent_args="3d -pmyrinet"
+outfile="fluent_test.out"
+mpp="true"
+`
+
+The following is an explanation of the parameters:
+
+ input is the name of the input
+file.
+
+ case is the name of the
+.cas file that the input file will utilize.
+
+ fluent_args are extra ANSYS FLUENT
+arguments. As shown in the previous example, you can specify the
+interconnect by using the -p interconnect
+command. The available interconnects include
+ethernet (the default),
+myrinet, class="monospace">
+infiniband, vendor,
+altix>, and
+crayx. The MPI is selected automatically, based
+on the specified interconnect.
+
+ outfile is the name of the file to which
+the standard output will be sent.
+
+ mpp="true" will tell the job script to
+execute the job across multiple processors. Â Â Â Â Â Â Â Â
+
+To run ANSYS Fluent in batch mode with user's config file you can
+utilize/modify the following script and execute it via the qsub
+command.
+
+`
+#!/bin/sh
+#PBS -l nodes=2:ppn=4
+#PBS -1 qprod
+#PBS -N $USE-Fluent-Project
+#PBS -A XX-YY-ZZ
+
+ cd $PBS_O_WORKDIR
+
+ #We assume that if they didn’t specify arguments then they should use the
+ #config file if [ "xx${input}${case}${mpp}${fluent_args}zz" = "xxzz" ]; then
+ if [ -f pbs_fluent.conf ]; then
+ . pbs_fluent.conf
+ else
+ printf "No command line arguments specified, "
+ printf "and no configuration file found. Exiting n"
+ fi
+ fi
+
+
+ #Augment the ANSYS FLUENT command line arguments case "$mpp" in
+ true)
+ #MPI job execution scenario
+ num_nodes=â€cat $PBS_NODEFILE | sort -u | wc -lâ€
+ cpus=â€expr $num_nodes * $NCPUSâ€
+ #Default arguments for mpp jobs, these should be changed to suit your
+ #needs.
+ fluent_args="-t${cpus} $fluent_args -cnf=$PBS_NODEFILE"
+ ;;
+ *)
+ #SMP case
+ #Default arguments for smp jobs, should be adjusted to suit your
+ #needs.
+ fluent_args="-t$NCPUS $fluent_args"
+ ;;
+ esac
+ #Default arguments for all jobs
+ fluent_args="-ssh -g -i $input $fluent_args"
+
+ echo "---------- Going to start a fluent job with the following settings:
+ Input: $input
+ Case: $case
+ Output: $outfile
+ Fluent arguments: $fluent_args"
+
+ #run the solver
+ /ansys_inc/v145/fluent/bin/fluent $fluent_args > $outfile
+`
+
+It runs the jobs out of the directory from which they are
+submitted (PBS_O_WORKDIR).
+
+4. Running Fluent in parralel
+-----------------------------
+
+Fluent could be run in parallel only under Academic Research license. To
+do so this ANSYS Academic Research license must be placed before ANSYS
+CFD license in user preferences. To make this change anslic_admin
+utility should be run
+
+`
+/ansys_inc/shared_les/licensing/lic_admin/anslic_admin
+`
+
+ANSLIC_ADMIN Utility will be run
+
+
+
+
+
+
+
+Â
+
+ANSYS Academic Research license should be moved up to the top of the
+list.
+
+Â
+
+
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-ls-dyna.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-ls-dyna.md
new file mode 100644
index 0000000000000000000000000000000000000000..397aa94adba08eb00f01dec704c3031739e8d110
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-ls-dyna.md
@@ -0,0 +1,86 @@
+ANSYS LS-DYNA
+=============
+
+[ANSYS
+LS-DYNA](http://www.ansys.com/Products/Simulation+Technology/Structural+Mechanics/Explicit+Dynamics/ANSYS+LS-DYNA)
+software provides convenient and easy-to-use access to the
+technology-rich, time-tested explicit solver without the need to contend
+with the complex input requirements of this sophisticated program.
+Introduced in 1996, ANSYS LS-DYNA capabilities have helped customers in
+numerous industries to resolve highly intricate design
+issues. >ANSYS Mechanical users have been able take advantage of
+complex explicit solutions for a long time utilizing the traditional
+ANSYS Parametric Design Language (APDL) environment. >These
+explicit capabilities are available to ANSYS Workbench users as well.
+The Workbench platform is a powerful, comprehensive, easy-to-use
+environment for engineering simulation. CAD import from all sources,
+geometry cleanup, automatic meshing, solution, parametric optimization,
+result visualization and comprehensive report generation are all
+available within a single fully interactive modern graphical user
+environment.
+
+To run ANSYS LS-DYNA in batch mode you can utilize/modify the
+default ansysdyna.pbs script and execute it via the qsub command.
+
+`
+#!/bin/bash
+#PBS -l nodes=2:ppn=16
+#PBS -q qprod
+#PBS -N $USER-DYNA-Project
+#PBS -A XX-YY-ZZ
+
+#! Mail to user when job terminate or abort
+#PBS -m ae
+
+#!change the working directory (default is home directory)
+#cd <working directory>
+WORK_DIR="/scratch/$USER/work"
+cd $WORK_DIR
+
+echo Running on host `hostname`
+echo Time is `date`
+echo Directory is `pwd`
+echo This jobs runs on the following processors:
+echo `cat $PBS_NODEFILE`
+
+#! Counts the number of processors
+NPROCS=`wc -l < $PBS_NODEFILE`
+
+echo This job has allocated $NPROCS nodes
+
+module load ansys
+
+#### Set number of processors per host listing
+#### (set to 1 as $PBS_NODEFILE lists each node twice if :ppn=2)
+procs_per_host=1
+#### Create host list
+hl=""
+for host in `cat $PBS_NODEFILE`
+do
+ if [ "$hl" = "" ]
+ then hl="$host:$procs_per_host"
+ else hl="${hl}:$host:$procs_per_host"
+ fi
+done
+
+echo Machines: $hl
+
+/ansys_inc/v145/ansys/bin/ansys145 -dis -lsdynampp i=input.k -machines $hl
+`
+
+Header of the pbs file (above) is common and description can be
+find on [this
+site](../../resource-allocation-and-job-execution/job-submission-and-execution.html)>.
+[SVS FEM](http://www.svsfem.cz) recommends to utilize
+sources by keywords: nodes, ppn. These keywords allows to address
+directly the number of nodes (computers) and cores (ppn) which will be
+utilized in the job. Also the rest of code assumes such structure of
+allocated resources.
+
+Working directory has to be created before sending pbs job into the
+queue. Input file should be in working directory or full path to input
+file has to be specified. Input file has to be defined by common LS-DYNA
+.**k** file which is attached to the ansys solver via parameter i=
+
+Â
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-mechanical-apdl.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-mechanical-apdl.md
new file mode 100644
index 0000000000000000000000000000000000000000..ac6357c2f9a6df62253546816739944985f0270e
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ansys-mechanical-apdl.md
@@ -0,0 +1,81 @@
+ANSYS MAPDL
+===========
+
+**[ANSYS
+Multiphysics](http://www.ansys.com/Products/Simulation+Technology/Structural+Mechanics/ANSYS+Multiphysics)**
+software offers a comprehensive product solution for both multiphysics
+and single-physics analysis. The product includes structural, thermal,
+fluid and both high- and low-frequency electromagnetic analysis. The
+product also contains solutions for both direct and sequentially coupled
+physics problems including direct coupled-field elements and the ANSYS
+multi-field solver.
+
+To run ANSYS MAPDL in batch mode you can utilize/modify the
+default mapdl.pbs script and execute it via the qsub command.
+
+`
+#!/bin/bash
+#PBS -l nodes=2:ppn=16
+#PBS -q qprod
+#PBS -N $USER-ANSYS-Project
+#PBS -A XX-YY-ZZ
+
+#! Mail to user when job terminate or abort
+#PBS -m ae
+
+#!change the working directory (default is home directory)
+#cd <working directory> (working directory must exists)
+WORK_DIR="/scratch/$USER/work"
+cd $WORK_DIR
+
+echo Running on host `hostname`
+echo Time is `date`
+echo Directory is `pwd`
+echo This jobs runs on the following processors:
+echo `cat $PBS_NODEFILE`
+
+module load ansys
+
+#### Set number of processors per host listing
+#### (set to 1 as $PBS_NODEFILE lists each node twice if :ppn=2)
+procs_per_host=1
+#### Create host list
+hl=""
+for host in `cat $PBS_NODEFILE`
+do
+ if [ "$hl" = "" ]
+ then hl="$host:$procs_per_host"
+ else hl="${hl}:$host:$procs_per_host"
+ fi
+done
+
+echo Machines: $hl
+
+#-i input.dat includes the input of analysis in APDL format
+#-o file.out is output file from ansys where all text outputs will be redirected
+#-p the name of license feature (aa_r=ANSYS Academic Research, ane3fl=Multiphysics(commercial), aa_r_dy=Academic AUTODYN)
+/ansys_inc/v145/ansys/bin/ansys145 -b -dis -p aa_r -i input.dat -o file.out -machines $hl -dir $WORK_DIR
+`
+
+Header of the pbs file (above) is common and description can be find on
+[this
+site](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+[SVS FEM](http://www.svsfem.cz) recommends to utilize
+sources by keywords: nodes, ppn. These keywords allows to address
+directly the number of nodes (computers) and cores (ppn) which will be
+utilized in the job. Also the rest of code assumes such structure of
+allocated resources.
+
+Working directory has to be created before sending pbs job into the
+queue. Input file should be in working directory or full path to input
+file has to be specified. Input file has to be defined by common APDL
+file which is attached to the ansys solver via parameter -i
+
+License** should be selected by parameter -p. Licensed products are
+the following: aa_r (ANSYS **Academic Research), ane3fl (ANSYS
+Multiphysics)-**Commercial**, aa_r_dy (ANSYS **Academic
+AUTODYN)>
+[ More
+ about licensing
+here](licensing.html)
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ls-dyna.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ls-dyna.md
new file mode 100644
index 0000000000000000000000000000000000000000..c2a86aa8574d0e7491af73766adce0e82c56bcd5
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/ansys/ls-dyna.md
@@ -0,0 +1,65 @@
+LS-DYNA
+=======
+
+[LS-DYNA](http://www.lstc.com/) is a multi-purpose,
+explicit and implicit finite element program used to analyze the
+nonlinear dynamic response of structures. Its fully automated contact
+analysis capability, a wide range of constitutive models to simulate a
+whole range of engineering materials (steels, composites, foams,
+concrete, etc.), error-checking features and the high scalability have
+enabled users worldwide to solve successfully many complex
+problems. >Additionally LS-DYNA is extensively used to simulate
+impacts on structures from drop tests, underwater shock, explosions or
+high-velocity impacts. Explosive forming, process engineering, accident
+reconstruction, vehicle dynamics, thermal brake disc analysis or nuclear
+safety are further areas in the broad range of possible applications. In
+leading-edge research LS-DYNA is used to investigate the behaviour of
+materials like composites, ceramics, concrete, or wood. Moreover, it is
+used in biomechanics, human modelling, molecular structures, casting,
+forging, or virtual testing.
+
+Anselm provides **1 commercial license of LS-DYNA without HPC**
+support now.Â
+
+To run LS-DYNA in batch mode you can utilize/modify the
+default lsdyna.pbs script and execute it via the qsub
+command.
+
+`
+#!/bin/bash
+#PBS -l nodes=1:ppn=16
+#PBS -q qprod
+#PBS -N $USER-LSDYNA-Project
+#PBS -A XX-YY-ZZ
+
+#! Mail to user when job terminate or abort
+#PBS -m ae
+
+#!change the working directory (default is home directory)
+#cd <working directory> (working directory must exists)
+WORK_DIR="/scratch/$USER/work"
+cd $WORK_DIR
+
+echo Running on host `hostname`
+echo Time is `date`
+echo Directory is `pwd`
+
+module load lsdyna
+
+/apps/engineering/lsdyna/lsdyna700s i=input.k
+`
+
+Header of the pbs file (above) is common and description can be find
+on [this
+site](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+[SVS FEM](http://www.svsfem.cz) recommends to utilize
+sources by keywords: nodes, ppn. These keywords allows to address
+directly the number of nodes (computers) and cores (ppn) which will be
+utilized in the job. Also the rest of code assumes such structure of
+allocated resources.
+
+Working directory has to be created before sending pbs job into the
+queue. Input file should be in working directory or full path to input
+file has to be specified. Input file has to be defined by common LS-DYNA
+.k** file which is attached to the LS-DYNA solver via parameter i=
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/chemistry/molpro.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/chemistry/molpro.md
new file mode 100644
index 0000000000000000000000000000000000000000..ff0be71faecd1c1b6374e9b2d92fbf44bece4eda
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/chemistry/molpro.md
@@ -0,0 +1,91 @@
+Molpro
+======
+
+Molpro is a complete system of ab initio programs for molecular
+electronic structure calculations.
+
+About Molpro
+------------
+
+Molpro is a software package used for accurate ab-initio quantum
+chemistry calculations. More information can be found at the [official
+webpage](http://www.molpro.net/).
+
+License
+-------
+
+Molpro software package is available only to users that have a valid
+license. Please contact support to enable access to Molpro if you have a
+valid license appropriate for running on our cluster (eg. >academic
+research group licence, parallel execution).
+
+To run Molpro, you need to have a valid license token present in
+" $HOME/.molpro/token". You can
+download the token from [Molpro
+website](https://www.molpro.net/licensee/?portal=licensee).
+
+Installed version
+-----------------
+
+Currently on Anselm is installed version 2010.1, patch level 45,
+parallel version compiled with Intel compilers and Intel MPI.
+
+Compilation parameters are default :
+
+ |Parameter|Value|
+ ------------------------------------------- |---|---|-------------------
+ |max number of atoms|200|
+ |max number of valence orbitals|300|
+ |max number of basis functions|4095|
+ |max number of states per symmmetry|20|
+ |max number of state symmetries|16|
+ |max number of records|200|
+ |max number of primitives|maxbfn x [2]|
+
+Â
+
+Running
+-------
+
+Molpro is compiled for parallel execution using MPI and OpenMP. By
+default, Molpro reads the number of allocated nodes from PBS and
+launches a data server on one node. On the remaining allocated nodes,
+compute processes are launched, one process per node, each with 16
+threads. You can modify this behavior by using -n, -t and helper-server
+options. Please refer to the [Molpro
+documentation](http://www.molpro.net/info/2010.1/doc/manual/node9.html)
+for more details.Â
+
+The OpenMP parallelization in Molpro is limited and has been observed to
+produce limited scaling. We therefore recommend to use MPI
+parallelization only. This can be achieved by passing option
+mpiprocs=16:ompthreads=1 to PBS.
+
+You are advised to use the -d option to point to a directory in [SCRATCH
+filesystem](../../storage.html). Molpro can produce a
+large amount of temporary data during its run, and it is important that
+these are placed in the fast scratch filesystem.
+
+### Example jobscript
+
+ #PBS -A IT4I-0-0
+ #PBS -q qprod
+ #PBS -l select=1:ncpus=16:mpiprocs=16:ompthreads=1
+
+ cd $PBS_O_WORKDIR
+
+ # load Molpro module
+ module add molpro
+
+ # create a directory in the SCRATCH filesystem
+ mkdir -p /scratch/$USER/$PBS_JOBID
+
+ # copy an example input
+ cp /apps/chem/molpro/2010.1/molprop_2010_1_Linux_x86_64_i8/examples/caffeine_opt_diis.com .
+
+ # run Molpro with default options
+ molpro -d /scratch/$USER/$PBS_JOBID caffeine_opt_diis.com
+
+ # delete scratch directory
+ rm -rf /scratch/$USER/$PBS_JOBIDÂ
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/chemistry/nwchem.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/chemistry/nwchem.md
new file mode 100644
index 0000000000000000000000000000000000000000..d52644e00840ab4ec5be1f3d856e2e2b82a83d45
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/chemistry/nwchem.md
@@ -0,0 +1,66 @@
+NWChem
+======
+
+High-Performance Computational Chemistry
+
+Introduction
+-------------------------
+
+NWChem aims to provide its users with computational chemistry
+tools that are scalable both in their ability to treat large scientific
+computational chemistry problems efficiently, and in their use of
+available parallel computing resources from high-performance parallel
+supercomputers to conventional workstation clusters.
+
+[Homepage](http://www.nwchem-sw.org/index.php/Main_Page)
+
+Installed versions
+------------------
+
+The following versions are currently installed :Â
+
+- 6.1.1, not recommended, problems have been observed with this
+ version
+
+- 6.3-rev2-patch1, current release with QMD patch applied. Compiled
+ with Intel compilers, MKL and Intel MPI
+
+- 6.3-rev2-patch1-openmpi, same as above, but compiled with OpenMPI
+ and NWChem provided BLAS instead of MKL. This version is expected to
+ be slower
+
+- 6.3-rev2-patch1-venus, this version contains only libraries for
+ VENUS interface linking. Does not provide standalone NWChem
+ executable
+
+For a current list of installed versions, execute :Â
+
+ module avail nwchem
+
+Running
+-------
+
+NWChem is compiled for parallel MPI execution. Normal procedure for MPI
+jobs applies. Sample jobscript :
+
+ #PBS -A IT4I-0-0
+ #PBS -q qprod
+ #PBS -l select=1:ncpus=16
+
+ module add nwchem/6.3-rev2-patch1
+ mpirun -np 16 nwchem h2o.nw
+
+Options
+--------------------
+
+Please refer to [the
+documentation](http://www.nwchem-sw.org/index.php/Release62:Top-level)Â and
+in the input file set the following directives :
+
+- >MEMORY : controls the amount of memory NWChem will use
+- >SCRATCH_DIR : set this to a directory in [SCRATCH
+ filesystem](../../storage.html#scratch)Â (or run the
+ calculation completely in a scratch directory). For certain
+ calculations, it might be advisable to reduce I/O by forcing
+ "direct" mode, eg. "scf direct"
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/compilers.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/compilers.md
new file mode 100644
index 0000000000000000000000000000000000000000..7450d0e1457ceb3e6d5230031834c6284a68c1e5
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/compilers.md
@@ -0,0 +1,163 @@
+Compilers
+=========
+
+Available compilers, including GNU, INTEL and UPC compilers
+
+
+
+Currently there are several compilers for different programming
+languages available on the Anselm cluster:
+
+- C/C++
+- Fortran 77/90/95
+- Unified Parallel C
+- Java
+- nVidia CUDA
+
+Â
+
+The C/C++ and Fortran compilers are divided into two main groups GNU and
+Intel.
+
+Intel Compilers
+---------------
+
+For information about the usage of Intel Compilers and other Intel
+products, please read the [Intel Parallel
+studio](intel-suite.html) page.
+
+GNU C/C++ and Fortran Compilers
+-------------------------------
+
+For compatibility reasons there are still available the original (old
+4.4.6-4) versions of GNU compilers as part of the OS. These are
+accessible in the search path by default.
+
+It is strongly recommended to use the up to date version (4.8.1) which
+comes with the module gcc:
+
+ $ module load gcc
+ $ gcc -v
+ $ g++ -v
+ $ gfortran -v
+
+With the module loaded two environment variables are predefined. One for
+maximum optimizations on the Anselm cluster architecture, and the other
+for debugging purposes:
+
+ $ echo $OPTFLAGS
+ -O3 -march=corei7-avx
+
+ $ echo $DEBUGFLAGS
+ -O0 -g
+
+For more informations about the possibilities of the compilers, please
+see the man pages.
+
+Unified Parallel C
+------------------
+
+UPC is supported by two compiler/runtime implementations:
+
+- GNU - SMP/multi-threading support only
+- Berkley - multi-node support as well as SMP/multi-threading support
+
+### GNU UPC Compiler
+
+To use the GNU UPC compiler and run the compiled binaries use the module
+gupc
+
+ $ module add gupc
+ $ gupc -v
+ $ g++ -v
+
+Simple program to test the compiler
+
+ $ cat count.upc
+
+ /* hello.upc - a simple UPC example */
+ #include <upc.h>
+ #include <stdio.h>
+
+ int main() {
+ Â if (MYTHREAD == 0) {
+ Â Â Â printf("Welcome to GNU UPC!!!n");
+ Â }
+ Â upc_barrier;
+ Â printf(" - Hello from thread %in", MYTHREAD);
+ Â return 0;
+ }
+
+To compile the example use
+
+ $ gupc -o count.upc.x count.upc
+
+To run the example with 5 threads issue
+
+ $ ./count.upc.x -fupc-threads-5
+
+For more informations see the man pages.
+
+### Berkley UPC Compiler
+
+To use the Berkley UPC compiler and runtime environment to run the
+binaries use the module bupc
+
+ $ module add bupc
+ $ upcc -version
+
+As default UPC network the "smp" is used. This is very quick and easy
+way for testing/debugging, but limited to one node only.
+
+For production runs, it is recommended to use the native Infiband
+implementation of UPC network "ibv". For testing/debugging using
+multiple nodes, the "mpi" UPC network is recommended. Please note, that
+the selection of the network is done at the compile time** and not at
+runtime (as expected)!
+
+Example UPC code:
+
+ $ cat hello.upc
+
+ /* hello.upc - a simple UPC example */
+ #include <upc.h>
+ #include <stdio.h>
+
+ int main() {
+ Â if (MYTHREAD == 0) {
+ Â Â Â printf("Welcome to Berkeley UPC!!!n");
+ Â }
+ Â upc_barrier;
+ Â printf(" - Hello from thread %in", MYTHREAD);
+ Â return 0;
+ }
+
+To compile the example with the "ibv" UPC network use
+
+ $ upcc -network=ibv -o hello.upc.x hello.upc
+
+To run the example with 5 threads issue
+
+ $ upcrun -n 5 ./hello.upc.x
+
+To run the example on two compute nodes using all 32 cores, with 32
+threads, issue
+
+ $ qsub -I -q qprod -A PROJECT_ID -l select=2:ncpus=16
+ $ module add bupc
+ $ upcrun -n 32 ./hello.upc.x
+
+Â For more informations see the man pages.
+
+Java
+----
+
+For information how to use Java (runtime and/or compiler), please read
+the [Java page](java.html).
+
+nVidia CUDA
+-----------
+
+For information how to work with nVidia CUDA, please read the [nVidia
+CUDA page](nvidia-cuda.html).
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/comsol/comsol-multiphysics.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/comsol/comsol-multiphysics.md
new file mode 100644
index 0000000000000000000000000000000000000000..25f1c4d0fd1cf538124f230a2297a279820118ce
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/comsol/comsol-multiphysics.md
@@ -0,0 +1,204 @@
+COMSOL Multiphysics®
+====================
+
+
+
+Introduction
+
+-------------------------
+
+[COMSOL](http://www.comsol.com)
+is a powerful environment for modelling and solving various engineering
+and scientific problems based on partial differential equations. COMSOL
+is designed to solve coupled or multiphysics phenomena. For many
+standard engineering problems COMSOL provides add-on products such as
+electrical, mechanical, fluid flow, and chemical
+applications.
+
+- >[Structural Mechanics
+ Module](http://www.comsol.com/structural-mechanics-module),
+
+
+- >[Heat Transfer
+ Module](http://www.comsol.com/heat-transfer-module),
+
+
+- >[CFD
+ Module](http://www.comsol.com/cfd-module),
+
+
+- >[Acoustics
+ Module](http://www.comsol.com/acoustics-module),
+
+
+- >and [many
+ others](http://www.comsol.com/products)
+
+COMSOL also allows an
+interface support for
+equation-based modelling of
+partial differential
+equations.
+
+Execution
+
+----------------------
+
+On the Anselm cluster COMSOL is available in the latest
+stable version. There are two variants of the release:
+
+- >**Non commercial** or so
+ called >**EDU
+ variant**>, which can be used for research
+ and educational purposes.
+
+- >**Commercial** or so called
+ >**COM variant**,
+ which can used also for commercial activities.
+ >**COM variant**
+ has only subset of features compared to the
+ >**EDU
+ variant**> available.
+
+ More about
+ licensing will be posted here
+ soon.
+
+
+To load the of COMSOL load the module
+
+`
+$ module load comsol
+`
+
+By default the **EDU
+variant**> will be loaded. If user needs other
+version or variant, load the particular version. To obtain the list of
+available versions use
+
+`
+$ module avail comsol
+`
+
+If user needs to prepare COMSOL jobs in the interactive mode
+it is recommend to use COMSOL on the compute nodes via PBS Pro
+scheduler. In order run the COMSOL Desktop GUI on Windows is recommended
+to use the [Virtual Network Computing
+(VNC)](https://docs.it4i.cz/anselm-cluster-documentation/software/comsol/resolveuid/11e53ad0d2fd4c5187537f4baeedff33).
+
+`
+$ xhost +
+$ qsub -I -X -A PROJECT_ID -q qprod -l select=1:ncpus=16
+$ module load comsol
+$ comsol
+`
+
+To run COMSOL in batch mode, without the COMSOL Desktop GUI
+environment, user can utilized the default (comsol.pbs) job script and
+execute it via the qsub command.
+
+`
+#!/bin/bash
+#PBS -l select=3:ncpus=16
+#PBS -q qprod
+#PBS -N JOB_NAME
+#PBS -AÂ PROJECT_ID
+
+cd /scratch/$USER/ || exit
+
+echo Time is `date`
+echo Directory is `pwd`
+echo '**PBS_NODEFILE***START*******'
+cat $PBS_NODEFILE
+echo '**PBS_NODEFILE***END*********'
+
+text_nodes < cat $PBS_NODEFILE
+
+module load comsol
+# module load comsol/43b-COM
+
+ntask=$(wc -l $PBS_NODEFILE)
+
+comsol -nn ${ntask} batch -configuration /tmp –mpiarg –rmk –mpiarg pbs -tmpdir /scratch/$USER/ -inputfile name_input_f.mph -outputfile name_output_f.mph -batchlog name_log_f.log
+`
+
+Working directory has to be created before sending the
+(comsol.pbs) job script into the queue. Input file (name_input_f.mph)
+has to be in working directory or full path to input file has to be
+specified. The appropriate path to the temp directory of the job has to
+be set by command option (-tmpdir).
+
+LiveLink™* *for MATLAB®^
+-------------------------
+
+COMSOL is the software package for the numerical solution of
+the partial differential equations. LiveLink for MATLAB allows
+connection to the
+COMSOL>><span><span><span><span>**®**</span>^
+API (Application Programming Interface) with the benefits of the
+programming language and computing environment of the MATLAB.
+
+LiveLink for MATLAB is available in both
+**EDU** and
+**COM**
+**variant** of the
+COMSOL release. On Anselm 1 commercial
+(>**COM**) license
+and the 5 educational
+(>**EDU**) licenses
+of LiveLink for MATLAB (please see the [ISV
+Licenses](../isv_licenses.html)) are available.
+Following example shows how to start COMSOL model from MATLAB via
+LiveLink in the interactive mode.
+
+`
+$ xhost +
+$ qsub -I -X -A PROJECT_ID -q qexp -l select=1:ncpus=16
+$ module load matlab
+$ module load comsol
+$ comsol server matlab
+`
+
+At the first time to launch the LiveLink for MATLAB
+(client-MATLAB/server-COMSOL connection) the login and password is
+requested and this information is not requested again.
+
+To run LiveLink for MATLAB in batch mode with
+(comsol_matlab.pbs) job script you can utilize/modify the following
+script and execute it via the qsub command.
+
+`
+#!/bin/bash
+#PBS -l select=3:ncpus=16
+#PBS -q qprod
+#PBS -N JOB_NAME
+#PBS -AÂ PROJECT_ID
+
+cd /scratch/$USER || exit
+
+echo Time is `date`
+echo Directory is `pwd`
+echo '**PBS_NODEFILE***START*******'
+cat $PBS_NODEFILE
+echo '**PBS_NODEFILE***END*********'
+
+text_nodes < cat $PBS_NODEFILE
+
+module load matlab
+module load comsol/43b-EDU
+
+ntask=$(wc -l $PBS_NODEFILE)
+
+comsol -nn ${ntask} server -configuration /tmp -mpiarg -rmk -mpiarg pbs -tmpdir /scratch/$USER &
+cd /apps/engineering/comsol/comsol43b/mli
+matlab -nodesktop -nosplash -r "mphstart; addpath /scratch/$USER; test_job"
+`
+
+This example shows how to run Livelink for MATLAB with following
+configuration: 3 nodes and 16 cores per node. Working directory has to
+be created before submitting (comsol_matlab.pbs) job script into the
+queue. Input file (test_job.m) has to be in working directory or full
+path to input file has to be specified. The Matlab command option (-r
+”mphstart”) created a connection with a COMSOL server using the default
+port number.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers.md
new file mode 100644
index 0000000000000000000000000000000000000000..f24688bd8fb51a85628a030f8f76379432820952
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers.md
@@ -0,0 +1,89 @@
+Debuggers and profilers summary
+===============================
+
+
+
+Introduction
+------------
+
+We provide state of the art programms and tools to develop, profile and
+debug HPC codes at IT4Innovations.
+On these pages, we provide an overview of the profiling and debugging
+tools available on Anslem at IT4I.
+
+Intel debugger
+--------------
+
+The intel debugger version 13.0 is available, via module intel. The
+debugger works for applications compiled with C and C++ compiler and the
+ifort fortran 77/90/95 compiler. The debugger provides java GUI
+environment. Use [X
+display](https://docs.it4i.cz/anselm-cluster-documentation/software/debuggers/resolveuid/11e53ad0d2fd4c5187537f4baeedff33)
+for running the GUI.
+
+ $ module load intel
+ $ idb
+
+Read more at the [Intel
+Debugger](intel-suite/intel-debugger.html) page.
+
+Allinea Forge (DDT/MAP)
+-----------------------
+
+Allinea DDT, is a commercial debugger primarily for debugging parallel
+MPI or OpenMP programs. It also has a support for GPU (CUDA) and Intel
+Xeon Phi accelerators. DDT provides all the standard debugging features
+(stack trace, breakpoints, watches, view variables, threads etc.) for
+every thread running as part of your program, or for every process -
+even if these processes are distributed across a cluster using an MPI
+implementation.
+
+ $ module load Forge
+ $ forge
+
+Read more at the [Allinea
+DDT](debuggers/allinea-ddt.html) page.
+
+Allinea Performance Reports
+---------------------------
+
+Allinea Performance Reports characterize the performance of HPC
+application runs. After executing your application through the tool, a
+synthetic HTML report is generated automatically, containing information
+about several metrics along with clear behavior statements and hints to
+help you improve the efficiency of your runs. Our license is limited to
+64 MPI processes.
+
+ $ module load PerformanceReports/6.0
+ $ perf-report mpirun -n 64 ./my_application argument01 argument02
+
+Read more at the [Allinea Performance
+Reports](debuggers/allinea-performance-reports.html)
+page.
+
+RougeWave Totalview
+-------------------
+
+TotalView is a source- and machine-level debugger for multi-process,
+multi-threaded programs. Its wide range of tools provides ways to
+analyze, organize, and test programs, making it easy to isolate and
+identify problems in individual threads and processes in programs of
+great complexity.
+
+ $ module load totalview
+ $ totalview
+
+Read more at the [Totalview](debuggers/total-view.html)
+page.
+
+Vampir trace analyzer
+---------------------
+
+Vampir is a GUI trace analyzer for traces in OTF format.
+
+ $ module load Vampir/8.5.0
+ $ vampir
+
+Read more at
+the [Vampir](../../salomon/software/debuggers/vampir.html) page.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/Snmekobrazovky20141204v12.56.36.png b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/Snmekobrazovky20141204v12.56.36.png
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diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/allinea-ddt.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/allinea-ddt.md
new file mode 100644
index 0000000000000000000000000000000000000000..237f66e9b50348ea499370f53427860f0c779afb
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/allinea-ddt.md
@@ -0,0 +1,129 @@
+Allinea Forge (DDT,MAP)
+=======================
+
+
+
+Allinea Forge consist of two tools - debugger DDT and profiler MAP.
+
+Allinea DDT, is a commercial debugger primarily for debugging parallel
+MPI or OpenMP programs. It also has a support for GPU (CUDA) and Intel
+Xeon Phi accelerators. DDT provides all the standard debugging features
+(stack trace, breakpoints, watches, view variables, threads etc.) for
+every thread running as part of your program, or for every process -
+even if these processes are distributed across a cluster using an MPI
+implementation.
+
+Allinea MAP is a profiler for C/C++/Fortran HPC codes. It is designed
+for profiling parallel code, which uses pthreads, OpenMP or MPI.
+
+License and Limitations for Anselm Users
+----------------------------------------
+
+On Anselm users can debug OpenMP or MPI code that runs up to 64 parallel
+processes. In case of debugging GPU or Xeon Phi accelerated codes the
+limit is 8 accelerators. These limitation means that:
+
+- 1 user can debug up 64 processes, or
+- 32 users can debug 2 processes, etc.
+
+In case of debugging on accelerators:
+
+- 1 user can debug on up to 8 accelerators, orÂ
+- 8 users can debug on single accelerator.Â
+
+Compiling Code to run with DDT
+------------------------------
+
+### Modules
+
+Load all necessary modules to compile the code. For example:Â
+
+ $ module load intel
+ $ module load impi ... or ... module load openmpi/X.X.X-icc
+
+Load the Allinea DDT module:
+
+ $ module load Forge
+
+Compile the code:
+
+`
+$ mpicc -g -O0 -o test_debug test.c
+
+$ mpif90 -g -O0 -o test_debug test.f
+`
+
+Â
+
+### Compiler flags
+
+Before debugging, you need to compile your code with theses flags:
+
+-g** : Generates extra debugging information usable by GDB. -g3**
+includes even more debugging information. This option is available for
+GNU and INTEL C/C++ and Fortran compilers.
+
+-O0** : Suppress all optimizations.**
+
+Â
+
+Starting a Job with DDT
+-----------------------
+
+Be sure to log in with an X window
+forwarding enabled. This could mean using the -X in the ssh: Â
+
+ $ ssh -X username@anselm.it4i.cz
+
+Other options is to access login node using VNC. Please see the detailed
+information on how to [use graphic user interface on
+Anselm](https://docs.it4i.cz/anselm-cluster-documentation/software/debuggers/resolveuid/11e53ad0d2fd4c5187537f4baeedff33)
+.
+
+From the login node an interactive session **with X windows forwarding**
+(-X option) can be started by following command:Â
+
+ $ qsub -I -X -A NONE-0-0 -q qexp -lselect=1:ncpus=16:mpiprocs=16,walltime=01:00:00Â
+
+Then launch the debugger with the ddt command followed by the name of
+the executable to debug:
+
+ $ ddt test_debug
+
+A submission window that appears have
+a prefilled path to the executable to debug. You can select the number
+of MPI processors and/or OpenMP threads on which to run and press run.
+Command line arguments to a program can be entered to the
+"Arguments "
+box.
+
+Â
+
+To start the debugging directly without the submission window, user can
+specify the debugging and execution parameters from the command line.
+For example the number of MPI processes is set by option "-np 4".
+Skipping the dialog is done by "-start" option. To see the list of the
+"ddt" command line parameters, run "ddt --help". Â
+
+ ddt -start -np 4 ./hello_debug_impi
+
+Â
+
+Documentation
+-------------
+
+Users can find original User Guide after loading the DDT module:Â
+
+ $DDTPATH/doc/userguide.pdf
+
+Â
+
+Â
+
+Â [1] Discipline, Magic, Inspiration and Science: Best Practice
+Debugging with Allinea DDT, Workshop conducted at LLNL by Allinea on May
+10, 2013,
+[link](https://computing.llnl.gov/tutorials/allineaDDT/index.html)
+
+Â
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/allinea-performance-reports.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/allinea-performance-reports.md
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index 0000000000000000000000000000000000000000..3c2e3ee645fc31b55e0cc6132c6a31f160674826
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/allinea-performance-reports.md
@@ -0,0 +1,77 @@
+Allinea Performance Reports
+===========================
+
+quick application profiling
+
+
+
+Introduction
+------------
+
+Allinea Performance Reports characterize the performance of HPC
+application runs. After executing your application through the tool, a
+synthetic HTML report is generated automatically, containing information
+about several metrics along with clear behavior statements and hints to
+help you improve the efficiency of your runs.
+
+The Allinea Performance Reports is most useful in profiling MPI
+programs.
+
+Our license is limited to 64 MPI processes.
+
+Modules
+-------
+
+Allinea Performance Reports version 6.0 is available
+
+ $ module load PerformanceReports/6.0
+
+The module sets up environment variables, required for using the Allinea
+Performance Reports. This particular command loads the default module,
+which is performance reports version 4.2.
+
+Usage
+-----
+
+Use the the perf-report wrapper on your (MPI) program.
+
+Instead of [running your MPI program the usual
+way](../mpi-1.html), use the the perf report wrapper:
+
+ $ perf-report mpirun ./mympiprog.x
+
+The mpi program will run as usual. The perf-report creates two
+additional files, in *.txt and *.html format, containing the
+performance report. Note that [demanding MPI codes should be run within
+the queue
+system](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+
+Example
+-------
+
+In this example, we will be profiling the mympiprog.x MPI program, using
+Allinea performance reports. Assume that the code is compiled with intel
+compilers and linked against intel MPI library:
+
+First, we allocate some nodes via the express queue:
+
+ $ qsub -q qexp -l select=2:ncpus=16:mpiprocs=16:ompthreads=1 -I
+ qsub: waiting for job 262197.dm2 to start
+ qsub: job 262197.dm2 ready
+
+Then we load the modules and run the program the usual way:
+
+ $ module load intel impi allinea-perf-report/4.2
+ $ mpirun ./mympiprog.x
+
+Now lets profile the code:
+
+ $ perf-report mpirun ./mympiprog.x
+
+Performance report files
+[mympiprog_32p*.txt](mympiprog_32p_2014-10-15_16-56.txt)
+and
+[mympiprog_32p*.html](mympiprog_32p_2014-10-15_16-56.html)
+were created. We can see that the code is very efficient on MPI and is
+CPU bounded.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/cube.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/cube.md
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index 0000000000000000000000000000000000000000..008d86c04f18021fcc536afb7da083be182cd959
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/cube.md
@@ -0,0 +1,65 @@
+CUBE
+====
+
+Introduction
+------------
+
+CUBE is a graphical performance report explorer for displaying data from
+Score-P and Scalasca (and other compatible tools). The name comes from
+the fact that it displays performance data in a three-dimensions :
+
+- **performance metric**, where a number of metrics are available,
+ such as communication time or cache misses,
+- **call path**, which contains the call tree of your program
+- s**ystem resource**, which contains system's nodes, processes and
+ threads, depending on the parallel programming model.
+
+Each dimension is organized in a tree, for example the time performance
+metric is divided into Execution time and Overhead time, call path
+dimension is organized by files and routines in your source code etc.
+
+
+
+*Figure 1. Screenshot of CUBE displaying data from Scalasca.*
+
+*
+*Each node in the tree is colored by severity (the color scheme is
+displayed at the bottom of the window, ranging from the least severe
+blue to the most severe being red). For example in Figure 1, we can see
+that most of the point-to-point MPI communication happens in routine
+exch_qbc, colored red.
+
+Installed versions
+------------------
+
+Currently, there are two versions of CUBE 4.2.3 available as
+[modules](../../environment-and-modules.html) :
+
+- class="s1"> cube/4.2.3-gcc,
+ compiled with GCC
+
+- class="s1"> cube/4.2.3-icc,
+ compiled with Intel compiler
+
+Usage
+-----
+
+CUBE is a graphical application. Refer to [Graphical User Interface
+documentation](https://docs.it4i.cz/anselm-cluster-documentation/software/debuggers/resolveuid/11e53ad0d2fd4c5187537f4baeedff33)
+for a list of methods to launch graphical applications on Anselm.
+
+Analyzing large data sets can consume large amount of CPU and RAM. Do
+not perform large analysis on login nodes.
+
+After loading the apropriate module, simply launch
+cube command, or alternatively you can use
+ scalasca -examine command to launch the
+GUI. Note that for Scalasca datasets, if you do not analyze the data
+with > scalasca
+-examine before to opening them with CUBE, not all
+performance data will be available.
+
+Â >References
+
+1. <http://www.scalasca.org/software/cube-4.x/download.html>
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/ddt1.png b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/ddt1.png
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diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/intel-performance-counter-monitor.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/intel-performance-counter-monitor.md
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--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/intel-performance-counter-monitor.md
@@ -0,0 +1,299 @@
+Intel Performance Counter Monitor
+=================================
+
+Introduction
+------------
+
+Intel PCM (Performance Counter Monitor) is a tool to monitor performance
+hardware counters on Intel>® processors, similar to
+[PAPI](papi.html). The difference between PCM and PAPI
+is that PCM supports only Intel hardware, but PCM can monitor also
+uncore metrics, like memory controllers and >QuickPath Interconnect
+links.
+
+Installed version
+------------------------------
+
+Currently installed version 2.6. To load the
+[module](../../environment-and-modules.html), issue :
+
+ $ module load intelpcm
+
+Command line tools
+------------------
+
+PCM provides a set of tools to monitor system/or application.Â
+
+### pcm-memory
+
+Measures memory bandwidth of your application or the whole system.
+Usage:
+
+ $ pcm-memory.x <delay>|[external_program parameters]
+
+Specify either a delay of updates in seconds or an external program to
+monitor. If you get an error about PMU in use, respond "y" and relaunch
+the program.
+
+Sample output:
+
+ ---------------------------------------||---------------------------------------
+ -- Socket 0 --||-- Socket 1 --
+ ---------------------------------------||---------------------------------------
+ ---------------------------------------||---------------------------------------
+ ---------------------------------------||---------------------------------------
+ -- Memory Performance Monitoring --||-- Memory Performance Monitoring --
+ ---------------------------------------||---------------------------------------
+ -- Mem Ch 0: Reads (MB/s): 2.44 --||-- Mem Ch 0: Reads (MB/s): 0.26 --
+ -- Writes(MB/s): 2.16 --||-- Writes(MB/s): 0.08 --
+ -- Mem Ch 1: Reads (MB/s): 0.35 --||-- Mem Ch 1: Reads (MB/s): 0.78 --
+ -- Writes(MB/s): 0.13 --||-- Writes(MB/s): 0.65 --
+ -- Mem Ch 2: Reads (MB/s): 0.32 --||-- Mem Ch 2: Reads (MB/s): 0.21 --
+ -- Writes(MB/s): 0.12 --||-- Writes(MB/s): 0.07 --
+ -- Mem Ch 3: Reads (MB/s): 0.36 --||-- Mem Ch 3: Reads (MB/s): 0.20 --
+ -- Writes(MB/s): 0.13 --||-- Writes(MB/s): 0.07 --
+ -- NODE0 Mem Read (MB/s): 3.47 --||-- NODE1 Mem Read (MB/s): 1.45 --
+ -- NODE0 Mem Write (MB/s): 2.55 --||-- NODE1 Mem Write (MB/s): 0.88 --
+ -- NODE0 P. Write (T/s) : 31506 --||-- NODE1 P. Write (T/s): 9099 --
+ -- NODE0 Memory (MB/s): 6.02 --||-- NODE1 Memory (MB/s): 2.33 --
+ ---------------------------------------||---------------------------------------
+ -- System Read Throughput(MB/s): 4.93 --
+ -- System Write Throughput(MB/s): 3.43 --
+ -- System Memory Throughput(MB/s): 8.35 --
+ ---------------------------------------||---------------------------------------Â
+
+### pcm-msr
+
+Command pcm-msr.x can be used to
+read/write model specific registers of the CPU.
+
+### pcm-numa
+
+NUMA monitoring utility does not work on Anselm.
+
+### pcm-pcie
+
+Can be used to monitor PCI Express bandwith. Usage:
+pcm-pcie.x <delay>
+
+### pcm-power
+
+Displays energy usage and thermal headroom for CPU and DRAM sockets.
+Usage:Â >Â pcm-power.x <delay> |
+<external program>
+
+### pcm
+
+This command provides an overview of performance counters and memory
+usage. >Usage: > pcm.x
+<delay> | <external program>
+
+Sample output :
+
+ $ pcm.x ./matrix
+
+ Intel(r) Performance Counter Monitor V2.6 (2013-11-04 13:43:31 +0100 ID=db05e43)
+
+ Copyright (c) 2009-2013 Intel Corporation
+
+ Number of physical cores: 16
+ Number of logical cores: 16
+ Threads (logical cores) per physical core: 1
+ Num sockets: 2
+ Core PMU (perfmon) version: 3
+ Number of core PMU generic (programmable) counters: 8
+ Width of generic (programmable) counters: 48 bits
+ Number of core PMU fixed counters: 3
+ Width of fixed counters: 48 bits
+ Nominal core frequency: 2400000000 Hz
+ Package thermal spec power: 115 Watt; Package minimum power: 51 Watt; Package maximum power: 180 Watt;
+ Socket 0: 1 memory controllers detected with total number of 4 channels. 2 QPI ports detected.
+ Socket 1: 1 memory controllers detected with total number of 4 channels. 2 QPI ports detected.
+ Number of PCM instances: 2
+ Max QPI link speed: 16.0 GBytes/second (8.0 GT/second)
+
+ Detected Intel(R) Xeon(R) CPU E5-2665 0 @ 2.40GHz "Intel(r) microarchitecture codename Sandy Bridge-EP/Jaketown"
+
+ Executing "./matrix" command:
+
+ Exit code: 0
+
+ EXEC : instructions per nominal CPU cycle
+ IPC : instructions per CPU cycle
+ FREQ : relation to nominal CPU frequency='unhalted clock ticks'/'invariant timer ticks' (includes Intel Turbo Boost)
+ AFREQ : relation to nominal CPU frequency while in active state (not in power-saving C state)='unhalted clock ticks'/'invariant timer ticks while in C0-state' (includes Intel Turbo Boost)
+ L3MISS: L3 cache misses
+ L2MISS: L2 cache misses (including other core's L2 cache *hits*)
+ L3HIT : L3 cache hit ratio (0.00-1.00)
+ L2HIT : L2 cache hit ratio (0.00-1.00)
+ L3CLK : ratio of CPU cycles lost due to L3 cache misses (0.00-1.00), in some cases could be >1.0 due to a higher memory latency
+ L2CLK : ratio of CPU cycles lost due to missing L2 cache but still hitting L3 cache (0.00-1.00)
+ READ : bytes read from memory controller (in GBytes)
+ WRITE : bytes written to memory controller (in GBytes)
+ TEMP : Temperature reading in 1 degree Celsius relative to the TjMax temperature (thermal headroom): 0 corresponds to the max temperature
+
+ Core (SKT) | EXEC | IPC | FREQ | AFREQ | L3MISS | L2MISS | L3HIT | L2HIT | L3CLK | L2CLK | READ | WRITE | TEMP
+
+ 0 0 0.00 0.64 0.01 0.80 5592 11 K 0.49 0.13 0.32 0.06 N/A N/A 67
+ 1 0 0.00 0.18 0.00 0.69 3086 5552 0.44 0.07 0.48 0.08 N/A N/A 68
+ 2 0 0.00 0.23 0.00 0.81 300 562 0.47 0.06 0.43 0.08 N/A N/A 67
+ 3 0 0.00 0.21 0.00 0.99 437 862 0.49 0.06 0.44 0.09 N/A N/A 73
+ 4 0 0.00 0.23 0.00 0.93 293 559 0.48 0.07 0.42 0.09 N/A N/A 73
+ 5 0 0.00 0.21 0.00 1.00 423 849 0.50 0.06 0.43 0.10 N/A N/A 69
+ 6 0 0.00 0.23 0.00 0.94 285 558 0.49 0.06 0.41 0.09 N/A N/A 71
+ 7 0 0.00 0.18 0.00 0.81 674 1130 0.40 0.05 0.53 0.08 N/A N/A 65
+ 8 1 0.00 0.47 0.01 1.26 6371 13 K 0.51 0.35 0.31 0.07 N/A N/A 64
+ 9 1 2.30 1.80 1.28 1.29 179 K 15 M 0.99 0.59 0.04 0.71 N/A N/A 60
+ 10 1 0.00 0.22 0.00 1.26 315 570 0.45 0.06 0.43 0.08 N/A N/A 67
+ 11 1 0.00 0.23 0.00 0.74 321 579 0.45 0.05 0.45 0.07 N/A N/A 66
+ 12 1 0.00 0.22 0.00 1.25 305 570 0.46 0.05 0.42 0.07 N/A N/A 68
+ 13 1 0.00 0.22 0.00 1.26 336 581 0.42 0.04 0.44 0.06 N/A N/A 69
+ 14 1 0.00 0.22 0.00 1.25 314 565 0.44 0.06 0.43 0.07 N/A N/A 69
+ 15 1 0.00 0.29 0.00 1.19 2815 6926 0.59 0.39 0.29 0.08 N/A N/A 69
+ -------------------------------------------------------------------------------------------------------------------
+ SKT 0 0.00 0.46 0.00 0.79 11 K 21 K 0.47 0.10 0.38 0.07 0.00 0.00 65
+ SKT 1 0.29 1.79 0.16 1.29 190 K 15 M 0.99 0.59 0.05 0.70 0.01 0.01 61
+ -------------------------------------------------------------------------------------------------------------------
+ TOTAL * 0.14 1.78 0.08 1.28 201 K 15 M 0.99 0.59 0.05 0.70 0.01 0.01 N/A
+
+ Instructions retired: 1345 M ; Active cycles: 755 M ; Time (TSC): 582 Mticks ; C0 (active,non-halted) core residency: 6.30 %
+
+ C1 core residency: 0.14 %; C3 core residency: 0.20 %; C6 core residency: 0.00 %; C7 core residency: 93.36 %;
+ C2 package residency: 48.81 %; C3 package residency: 0.00 %; C6 package residency: 0.00 %; C7 package residency: 0.00 %;
+
+ PHYSICAL CORE IPC : 1.78 => corresponds to 44.50 % utilization for cores in active state
+ Instructions per nominal CPU cycle: 0.14 => corresponds to 3.60 % core utilization over time interval
+
+ Intel(r) QPI data traffic estimation in bytes (data traffic coming to CPU/socket through QPI links):
+
+ QPI0 QPI1 | QPI0 QPI1
+ ----------------------------------------------------------------------------------------------
+ SKT 0 0 0 | 0% 0%
+ SKT 1 0 0 | 0% 0%
+ ----------------------------------------------------------------------------------------------
+ Total QPI incoming data traffic: 0 QPI data traffic/Memory controller traffic: 0.00
+
+ Intel(r) QPI traffic estimation in bytes (data and non-data traffic outgoing from CPU/socket through QPI links):
+
+ QPI0 QPI1 | QPI0 QPI1
+ ----------------------------------------------------------------------------------------------
+ SKT 0 0 0 | 0% 0%
+ SKT 1 0 0 | 0% 0%
+ ----------------------------------------------------------------------------------------------
+ Total QPI outgoing data and non-data traffic: 0
+
+ ----------------------------------------------------------------------------------------------
+ SKT 0 package consumed 4.06 Joules
+ SKT 1 package consumed 9.40 Joules
+ ----------------------------------------------------------------------------------------------
+ TOTAL: 13.46 Joules
+
+ ----------------------------------------------------------------------------------------------
+ SKT 0 DIMMs consumed 4.18 Joules
+ SKT 1 DIMMs consumed 4.28 Joules
+ ----------------------------------------------------------------------------------------------
+ TOTAL: 8.47 Joules
+ Cleaning up
+
+Â
+
+### pcm-sensor
+
+Can be used as a sensor for ksysguard GUI, which is currently not
+installed on Anselm.Â
+
+API
+---
+
+In a similar fashion to PAPI, PCM provides a C++ API to access the
+performance counter from within your application. Refer to the [doxygen
+documentation](http://intel-pcm-api-documentation.github.io/classPCM.html)
+for details of the API.
+
+Due to security limitations, using PCM API to monitor your applications
+is currently not possible on Anselm. (The application must be run as
+root user)
+
+Sample program using the API :
+
+ #include <stdlib.h>
+ #include <stdio.h>
+ #include "cpucounters.h"
+
+ #define SIZE 1000
+
+ using namespace std;
+
+ int main(int argc, char **argv) {
+ float matrixa[SIZE][SIZE], matrixb[SIZE][SIZE], mresult[SIZE][SIZE];
+ float real_time, proc_time, mflops;
+ long long flpins;
+ int retval;
+ int i,j,k;
+
+ PCM * m = PCM::getInstance();
+
+ if (m->program() != PCM::Success) return 1;
+
+ SystemCounterState before_sstate = getSystemCounterState();
+
+ /* Initialize the Matrix arrays */
+ for ( i=0; i<SIZE*SIZE; i++ ){
+ mresult[0][i] = 0.0;
+ matrixa[0][i] = matrixb[0][i] = rand()*(float)1.1; }
+
+ /* A naive Matrix-Matrix multiplication */
+ for (i=0;i<SIZE;i++)
+ for(j=0;j<SIZE;j++)
+ for(k=0;k<SIZE;k++)
+ mresult[i][j]=mresult[i][j] + matrixa[i][k]*matrixb[k][j];
+
+ SystemCounterState after_sstate = getSystemCounterState();
+
+ cout << "Instructions per clock:" << getIPC(before_sstate,after_sstate)
+ << "L3 cache hit ratio:" << getL3CacheHitRatio(before_sstate,after_sstate)
+ << "Bytes read:" << getBytesReadFromMC(before_sstate,after_sstate);
+
+ for (i=0; i<SIZE;i++)
+ for (j=0; j<SIZE; j++)
+ if (mresult[i][j] == -1) printf("x");
+
+ return 0;
+ }
+
+Compile it with :
+
+ $ icc matrix.cpp -o matrix -lpthread -lpcm
+
+Sample output :Â
+
+ $ ./matrix
+ Number of physical cores: 16
+ Number of logical cores: 16
+ Threads (logical cores) per physical core: 1
+ Num sockets: 2
+ Core PMU (perfmon) version: 3
+ Number of core PMU generic (programmable) counters: 8
+ Width of generic (programmable) counters: 48 bits
+ Number of core PMU fixed counters: 3
+ Width of fixed counters: 48 bits
+ Nominal core frequency: 2400000000 Hz
+ Package thermal spec power: 115 Watt; Package minimum power: 51 Watt; Package maximum power: 180 Watt;
+ Socket 0: 1 memory controllers detected with total number of 4 channels. 2 QPI ports detected.
+ Socket 1: 1 memory controllers detected with total number of 4 channels. 2 QPI ports detected.
+ Number of PCM instances: 2
+ Max QPI link speed: 16.0 GBytes/second (8.0 GT/second)
+ Instructions per clock:1.7
+ L3 cache hit ratio:1.0
+ Bytes read:12513408
+
+References
+----------
+
+1. <https://software.intel.com/en-us/articles/intel-performance-counter-monitor-a-better-way-to-measure-cpu-utilization>
+2. <https://software.intel.com/sites/default/files/m/3/2/2/xeon-e5-2600-uncore-guide.pdf> Intel®
+ Xeon® Processor E5-2600 Product Family Uncore Performance
+ Monitoring Guide.
+3. <http://intel-pcm-api-documentation.github.io/classPCM.html>Â API
+ Documentation
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/intel-vtune-amplifier.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/intel-vtune-amplifier.md
new file mode 100644
index 0000000000000000000000000000000000000000..b22b73f2b336d267a0279892d251d20b30381838
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/intel-vtune-amplifier.md
@@ -0,0 +1,109 @@
+Intel VTune Amplifier
+=====================
+
+
+
+Introduction
+------------
+
+Intel*® *VTune™ >Amplifier, part of Intel Parallel studio, is a GUI
+profiling tool designed for Intel processors. It offers a graphical
+performance analysis of single core and multithreaded applications. A
+highlight of the features:
+
+- Hotspot analysis
+- Locks and waits analysis
+- Low level specific counters, such as branch analysis and memory
+ bandwidth
+- Power usage analysis - frequency and sleep states.
+
+
+
+Usage
+-----
+
+To launch the GUI, first load the module:
+
+ $ module add VTune/2016_update1
+
+ class="s1">and launch the GUI :
+
+ $Â amplxe-gui
+
+To profile an application with VTune Amplifier, special kernel
+modules need to be loaded. The modules are not loaded on Anselm login
+nodes, thus direct profiling on login nodes is not possible. Use VTune
+on compute nodes and refer to the documentation on [using GUI
+applications](https://docs.it4i.cz/anselm-cluster-documentation/software/debuggers/resolveuid/11e53ad0d2fd4c5187537f4baeedff33).
+
+The GUI will open in new window. Click on "*New Project...*" to
+create a new project. After clicking *OK*, a new window with project
+properties will appear. Â At "*Application:*", select the bath to your
+binary you want to profile (the binary should be compiled with -g flag).
+Some additional options such as command line arguments can be selected.
+At "*Managed code profiling mode:*" select "*Native*" (unless you want
+to profile managed mode .NET/Mono applications). After clicking *OK*,
+your project is created.
+
+To run a new analysis, click "*New analysis...*". You will see a list of
+possible analysis. Some of them will not be possible on the current CPU
+(eg. Intel Atom analysis is not possible on Sandy Bridge CPU), the GUI
+will show an error box if you select the wrong analysis. For example,
+select "*Advanced Hotspots*". Clicking on *Start *will start profiling
+of the application.
+
+Remote Analysis
+---------------
+
+VTune Amplifier also allows a form of remote analysis. In this mode,
+data for analysis is collected from the command line without GUI, and
+the results are then loaded to GUI on another machine. This allows
+profiling without interactive graphical jobs. To perform a remote
+analysis, launch a GUI somewhere, open the new analysis window and then
+click the button "*Command line*" in bottom right corner. It will show
+the command line needed to perform the selected analysis.
+
+The command line will look like this:
+
+ /apps/all/VTune/2016_update1/vtune_amplifier_xe_2016.1.1.434111/bin64/amplxe-cl -collect advanced-hotspots -knob collection-detail=stack-and-callcount -mrte-mode=native -target-duration-type=veryshort -app-working-dir /home/sta545/test -- /home/sta545/test_pgsesv
+
+Copy the line to clipboard and then you can paste it in your jobscript
+or in command line. After the collection is run, open the GUI once
+again, click the menu button in the upper right corner, and select
+"*Open > Result...*". The GUI will load the results from the run.
+
+Xeon Phi
+--------
+
+This section is outdated. It will be updated with new information soon.
+
+It is possible to analyze both native and offload Xeon Phi applications.
+For offload mode, just specify the path to the binary. For native mode,
+you need to specify in project properties:
+
+Application: ssh
+
+Application parameters: mic0 source ~/.profile
+&& /path/to/your/bin
+
+Note that we include source ~/.profile
+in the command to setup environment paths [as described
+here](../intel-xeon-phi.html).Â
+
+If the analysis is interrupted or aborted, further analysis on the card
+might be impossible and you will get errors like "ERROR connecting to
+MIC card". In this case please contact our support to reboot the MIC
+card.
+
+You may also use remote analysis to collect data from the MIC and then
+analyze it in the GUI later :
+
+ $ amplxe-cl -collect knc-hotspots -no-auto-finalize -- ssh mic0
+ "export LD_LIBRARY_PATH=/apps/intel/composer_xe_2015.2.164/compiler/lib/mic/:/apps/intel/composer_xe_2015.2.164/mkl/lib/mic/; export KMP_AFFINITY=compact; /tmp/app.mic"
+
+References
+----------
+
+1. ><https://www.rcac.purdue.edu/tutorials/phi/PerformanceTuningXeonPhi-Tullos.pdf>Â Performance
+ Tuning for Intel® Xeon Phi™ Coprocessors
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/papi.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/papi.md
new file mode 100644
index 0000000000000000000000000000000000000000..df34e4232f4b6059c4522aa033e9e8bf0fc5c08f
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/papi.md
@@ -0,0 +1,267 @@
+PAPI
+====
+
+
+
+Introduction
+------------
+
+ dir="auto">Performance Application Programming
+Interface >(PAPI)  is a portable interface to access
+hardware performance counters (such as instruction counts and cache
+misses) found in most modern architectures. With the new component
+framework, PAPI is not limited only to CPU counters, but offers also
+components for CUDA, network, Infiniband etc.
+
+PAPI provides two levels of interface - a simpler, high level
+interface and more detailed low level interface.
+
+PAPI can be used with parallel as well as serial programs.
+
+Usage
+-----
+
+To use PAPI, load
+[module](../../environment-and-modules.html)
+papi :
+
+ $ module load papi
+
+This will load the default version. Execute
+module avail papi for a list of installed
+versions.
+
+Utilites
+--------
+
+The bin directory of PAPI (which is
+automatically added to $PATH upon
+loading the module) contains various utilites.
+
+### papi_avail
+
+Prints which preset events are available on the current CPU. The third
+column indicated whether the preset event is available on the current
+CPU.
+
+ $ papi_avail
+ Available events and hardware information.
+ --------------------------------------------------------------------------------
+ PAPI Version : 5.3.2.0
+ Vendor string and code : GenuineIntel (1)
+ Model string and code : Intel(R) Xeon(R) CPU E5-2670 0 @ 2.60GHz (45)
+ CPU Revision : 7.000000
+ CPUID Info : Family: 6 Model: 45 Stepping: 7
+ CPU Max Megahertz : 2601
+ CPU Min Megahertz : 1200
+ Hdw Threads per core : 1
+ Cores per Socket : 8
+ Sockets : 2
+ NUMA Nodes : 2
+ CPUs per Node : 8
+ Total CPUs : 16
+ Running in a VM : no
+ Number Hardware Counters : 11
+ Max Multiplex Counters : 32
+ --------------------------------------------------------------------------------
+ Name Code Avail Deriv Description (Note)
+ PAPI_L1_DCM 0x80000000 Yes No Level 1 data cache misses
+ PAPI_L1_ICM 0x80000001 Yes No Level 1 instruction cache misses
+ PAPI_L2_DCM 0x80000002 Yes Yes Level 2 data cache misses
+ PAPI_L2_ICM 0x80000003 Yes No Level 2 instruction cache misses
+ PAPI_L3_DCM 0x80000004 No No Level 3 data cache misses
+ PAPI_L3_ICM 0x80000005 No No Level 3 instruction cache misses
+ PAPI_L1_TCM 0x80000006 Yes Yes Level 1 cache misses
+ PAPI_L2_TCM 0x80000007 Yes No Level 2 cache misses
+ PAPI_L3_TCM 0x80000008 Yes No Level 3 cache misses
+ ....Â
+
+### papi_native_avail
+
+Prints which native events are available on the current
+CPU.
+
+### class="s1">papi_cost
+
+Measures the cost (in cycles) of basic PAPI operations.
+
+###papi_mem_info
+
+Prints information about the memory architecture of the current
+CPU.
+
+PAPI API
+--------
+
+PAPI provides two kinds of events:Â
+
+- **Preset events** is a set of predefined common CPU events,
+ >standardized across platforms.
+- **Native events **is a set of all events supported by the
+ current hardware. This is a larger set of features than preset. For
+ other components than CPU, only native events are usually available.
+
+To use PAPI in your application, you need to link the appropriate
+include file.
+
+- papi.h for C
+- f77papi.h for Fortran 77
+- f90papi.h for Fortran 90
+- fpapi.h for Fortran with preprocessor
+
+The include path is automatically added by papi module to
+$INCLUDE.
+
+### High level API
+
+Please refer
+to <http://icl.cs.utk.edu/projects/papi/wiki/PAPIC:High_Level> for a
+description of the High level API.
+
+### Low level API
+
+Please refer
+to <http://icl.cs.utk.edu/projects/papi/wiki/PAPIC:Low_Level> for a
+description of the Low level API.
+
+### Timers
+
+PAPI provides the most accurate timers the platform can support.
+See <http://icl.cs.utk.edu/projects/papi/wiki/PAPIC:Timers>
+
+### System information
+
+PAPI can be used to query some system infromation, such as CPU name and
+MHz.
+See <http://icl.cs.utk.edu/projects/papi/wiki/PAPIC:System_Information>
+
+Example
+-------
+
+The following example prints MFLOPS rate of a naive matrix-matrix
+multiplication :
+
+ #include <stdlib.h>
+ #include <stdio.h>
+ #include "papi.h"
+ #define SIZE 1000
+
+ int main(int argc, char **argv) {
+ float matrixa[SIZE][SIZE], matrixb[SIZE][SIZE], mresult[SIZE][SIZE];
+ float real_time, proc_time, mflops;
+ long long flpins;
+ int retval;
+ int i,j,k;
+
+ /* Initialize the Matrix arrays */
+ for ( i=0; i<SIZE*SIZE; i++ ){
+ mresult[0][i] = 0.0;
+ matrixa[0][i] = matrixb[0][i] = rand()*(float)1.1;Â
+ }
+ Â
+ /* Setup PAPI library and begin collecting data from the counters */
+ if((retval=PAPI_flops( &real_time, &proc_time, &flpins, &mflops))<PAPI_OK)
+ printf("Error!");
+
+ /* A naive Matrix-Matrix multiplication */
+ for (i=0;i<SIZE;i++)
+ for(j=0;j<SIZE;j++)
+ for(k=0;k<SIZE;k++)
+ mresult[i][j]=mresult[i][j] + matrixa[i][k]*matrixb[k][j];
+
+ /* Collect the data into the variables passed in */
+ if((retval=PAPI_flops( &real_time, &proc_time, &flpins, &mflops))<PAPI_OK)
+ printf("Error!");
+
+ printf("Real_time:t%fnProc_time:t%fnTotal flpins:t%lldnMFLOPS:tt%fn", real_time, proc_time, flpins, mflops);
+ PAPI_shutdown();
+ return 0;
+ }
+
+Â Now compile and run the example :
+
+ $ gcc matrix.c -o matrix -lpapi
+ $ ./matrix
+ Real_time: 8.852785
+ Proc_time: 8.850000
+ Total flpins: 6012390908
+ MFLOPS: 679.366211Â
+
+Let's try with optimizations enabled :
+
+ $ gcc -O3 matrix.c -o matrix -lpapi
+ $ ./matrix
+ Real_time: 0.000020
+ Proc_time: 0.000000
+ Total flpins: 6
+ MFLOPS: inf
+
+Now we see a seemingly strange result - the multiplication took no time
+and only 6 floating point instructions were issued. This is because the
+compiler optimizations have completely removed the multiplication loop,
+as the result is actually not used anywhere in the program. We can fix
+this by adding some "dummy" code at the end of the Matrix-Matrix
+multiplication routine :
+
+ for (i=0; i<SIZE;i++)
+ for (j=0; j<SIZE; j++)
+ if (mresult[i][j] == -1.0) printf("x");
+
+Now the compiler won't remove the multiplication loop. (However it is
+still not that smart to see that the result won't ever be negative). Now
+run the code again:
+
+ $ gcc -O3 matrix.c -o matrix -lpapi
+ $ ./matrix
+ Real_time: 8.795956
+ Proc_time: 8.790000
+ Total flpins: 18700983160
+ MFLOPS: 2127.529297Â
+
+### Intel Xeon Phi
+
+PAPI currently supports only a subset of counters on the Intel Xeon Phi
+processor compared to Intel Xeon, for example the floating point
+operations counter is missing.
+
+To use PAPI in [Intel Xeon
+Phi](../intel-xeon-phi.html)Â native applications, you
+need to load module with " -mic" suffix,
+for example " papi/5.3.2-mic" :
+
+ $ module load papi/5.3.2-mic
+
+Then, compile your application in the following way:
+
+ $ module load intel
+ $ icc -mmic -Wl,-rpath,/apps/intel/composer_xe_2013.5.192/compiler/lib/mic matrix-mic.c -o matrix-mic -lpapi -lpfm
+
+To execute the application on MIC, you need to manually setÂ
+LD_LIBRARY_PATH :
+
+ $Â qsub -q qmic -A NONE-0-0 -I
+ $ ssh mic0
+ $ export LD_LIBRARY_PATH=/apps/tools/papi/5.4.0-mic/lib/Â
+ $ ./matrix-micÂ
+
+Alternatively, you can link PAPI statically (
+-static flag), then
+LD_LIBRARY_PATH does not need to be set.
+
+You can also execute the PAPI tools on MIC :
+
+ $ /apps/tools/papi/5.4.0-mic/bin/papi_native_avail
+
+To use PAPI in offload mode, you need to provide both host and MIC
+versions of PAPI:
+
+ $ module load papi/5.4.0
+ $ icc matrix-offload.c -o matrix-offload -offload-option,mic,compiler,"-L$PAPI_HOME-mic/lib -lpapi" -lpapi
+
+References
+----------
+
+1. <http://icl.cs.utk.edu/papi/>Â Main project page
+2. <http://icl.cs.utk.edu/projects/papi/wiki/Main_Page>Â Wiki
+3. <http://icl.cs.utk.edu/papi/docs/> API Documentation
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/scalasca.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/scalasca.md
new file mode 100644
index 0000000000000000000000000000000000000000..df942821880a9b653310e3d01b1489cf13665e76
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/scalasca.md
@@ -0,0 +1,107 @@
+Scalasca
+========
+
+Introduction
+-------------------------
+
+[Scalasca](http://www.scalasca.org/) is a software tool
+that supports the performance optimization of parallel programs by
+measuring and analyzing their runtime behavior. The analysis identifies
+potential performance bottlenecks – in particular those concerning
+communication and synchronization – and offers guidance in exploring
+their causes.
+
+Scalasca supports profiling of MPI, OpenMP and hybrid MPI+OpenMP
+applications.
+
+Installed versions
+------------------
+
+There are currently two versions of Scalasca 2.0
+[modules](../../environment-and-modules.html) installed
+on Anselm:
+
+- class="s1">
+ scalasca2/2.0-gcc-openmpi, for usage with
+ [GNU Compiler](../compilers.html) and
+ [OpenMPI](../mpi-1/Running_OpenMPI.html),
+
+- class="s1">
+ scalasca2/2.0-icc-impi, for usage with
+ [Intel Compiler](../compilers.html) and [Intel
+ MPI](../mpi-1/running-mpich2.html).
+
+Usage
+-----
+
+Profiling a parallel application with Scalasca consists of three steps:
+
+1. Instrumentation, compiling the application such way, that the
+ profiling data can be generated.
+2. Runtime measurement, running the application with the Scalasca
+ profiler to collect performance data.
+3. Analysis of reports
+
+### Instrumentation
+
+Instrumentation via " scalasca
+-instrument" is discouraged. Use [Score-P
+instrumentation](score-p.html).
+
+### Runtime measurement
+
+After the application is instrumented, runtime measurement can be
+performed with the " scalasca -analyze"
+command. The syntax is :
+
+ scalasca -analyze [scalasca options]
+[launcher] [launcher options] [program] [program options]
+
+An example :
+
+ $ scalasca -analyze mpirun -np 4 ./mympiprogram
+
+Some notable Scalsca options are:
+
+-t Enable trace data collection. By default, only summary data are
+collected.
+-e <directory> Specify a directory to save the collected data to.
+By default, Scalasca saves the data to a directory with
+prefix >scorep_, followed by name of the executable and launch
+configuration.
+
+Scalasca can generate a huge amount of data, especially if tracing is
+enabled. Please consider saving the data to a [scratch
+directory](../../storage.html).
+
+### Analysis of reports
+
+For the analysis, you must have [Score-P](score-p.html)
+and [CUBE](cube.html) modules loaded. The analysis is
+done in two steps, first, the data is preprocessed and then CUBE GUI
+tool is launched.
+
+To launch the analysis, run :
+
+`
+scalasca -examine [options] <experiment_directory>
+`
+
+If you do not wish to launch the GUI tool, use the "-s" option :
+
+`
+scalasca -examine -s <experiment_directory>
+`
+
+Alternatively you can open CUBE and load the data directly from here.
+Keep in mind that in that case the preprocessing is not done and not all
+metrics will be shown in the viewer.
+
+Refer to [CUBE documentation](cube.html)Â on usage of the
+GUI viewer.
+
+References
+----------
+
+1. <http://www.scalasca.org/>
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/score-p.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/score-p.md
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index 0000000000000000000000000000000000000000..0462b82ff2e97f3e2c0078740dc241bae80272e2
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/score-p.md
@@ -0,0 +1,148 @@
+Score-P
+=======
+
+Introduction
+------------
+
+The [Score-P measurement
+infrastructure](http://www.vi-hps.org/projects/score-p/)
+is a highly scalable and easy-to-use tool suite for profiling, event
+tracing, and online analysis of HPC applications.Â
+
+Score-P can be used as an instrumentation tool for
+[Scalasca](scalasca.html).
+
+Installed versions
+------------------
+
+There are currently two versions of Score-P version 1.2.6
+[modules](../../environment-and-modules.html)Â installed
+on Anselm :
+
+- class="s1">scorep/1.2.3-gcc-openmpi>, for usage
+ with [GNU
+ Compiler](../compilers.html)> and [OpenMPI](../mpi-1/Running_OpenMPI.html){.internal>,
+
+- class="s1">scorep/1.2.3-icc-impi>, for usage
+ with [Intel
+ Compiler](../compilers.html)> and [Intel
+ MPI](../mpi-1/running-mpich2.html)>.
+
+Instrumentation
+---------------
+
+There are three ways to instrument your parallel applications in
+order to enable performance data collection :
+
+1. >Automated instrumentation using compiler
+2. >Manual instrumentation using API calls
+3. >Manual instrumentation using directives
+
+### Automated instrumentation
+
+is the easiest method. Score-P will automatically add instrumentation to
+every routine entry and exit using compiler hooks, and will intercept
+MPI calls and OpenMP regions. This method might, however, produce a
+large number of data. If you want to focus on profiler a specific
+regions of your code, consider using the manual instrumentation methods.
+To use automated instrumentation, simply prepend
+scorep to your compilation command. For
+example, replace :Â
+
+`
+$ mpif90 -c foo.f90
+$ mpif90 -c bar.f90
+$ mpif90 -o myapp foo.o bar.o
+`
+
+with :
+
+`
+$ scorep mpif90 -c foo.f90
+$ scorep mpif90 -c bar.f90
+$ scorep mpif90 -o myapp foo.o bar.o
+`
+
+Usually your program is compiled using a Makefile or similar script, so
+it advisable to add the scorep command to
+your definition of variables CC,
+CXX, class="monospace">FCC etc.
+
+It is important that scorep is prepended
+also to the linking command, in order to link with Score-P
+instrumentation libraries.
+
+###Manual instrumentation using API calls
+
+To use this kind of instrumentation, use
+scorep with switch
+--user. You will then mark regions to be
+instrumented by inserting API calls.
+
+An example in C/C++ :
+
+ #include <scorep/SCOREP_User.h>
+ void foo()
+ {
+ SCOREP_USER_REGION_DEFINE( my_region_handle )
+ // more declarations
+ SCOREP_USER_REGION_BEGIN( my_region_handle, "foo", SCOREP_USER_REGION_TYPE_COMMON )
+ // do something
+ SCOREP_USER_REGION_END( my_region_handle )
+ }
+
+Â and Fortran :
+
+ #include "scorep/SCOREP_User.inc"
+ subroutine foo
+ SCOREP_USER_REGION_DEFINE( my_region_handle )
+ ! more declarations
+ SCOREP_USER_REGION_BEGIN( my_region_handle, "foo", SCOREP_USER_REGION_TYPE_COMMON )
+ ! do something
+ SCOREP_USER_REGION_END( my_region_handle )
+ end subroutine foo
+
+Please refer to the [documentation for description of the
+API](https://silc.zih.tu-dresden.de/scorep-current/pdf/scorep.pdf).
+
+###Manual instrumentation using directives
+
+This method uses POMP2 directives to mark regions to be instrumented. To
+use this method, use command scorep
+--pomp.
+
+Example directives in C/C++ :
+
+ void foo(...)
+ {
+ /* declarations */
+ #pragma pomp inst begin(foo)
+ ...
+ if (<condition>)
+ {
+ #pragma pomp inst altend(foo)
+ return;
+ }
+ ...
+ #pragma pomp inst end(foo)
+ }
+
+and in Fortran :
+
+ subroutine foo(...)
+ !declarations
+ !POMP$ INST BEGIN(foo)
+ ...
+ if (<condition>) then
+ !POMP$ INST ALTEND(foo)
+ return
+ end if
+ ...
+ !POMP$ INST END(foo)
+ end subroutine foo
+
+The directives are ignored if the program is compiled without Score-P.
+Again, please refer to the
+[documentation](https://silc.zih.tu-dresden.de/scorep-current/pdf/scorep.pdf)
+for a more elaborate description.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/summary.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/summary.md
new file mode 100644
index 0000000000000000000000000000000000000000..2b1f34c23030b3dc1f0e1ad95218e114964272ff
--- /dev/null
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@@ -0,0 +1,86 @@
+Debuggers and profilers summary
+===============================
+
+
+
+Introduction
+------------
+
+We provide state of the art programms and tools to develop, profile and
+debug HPC codes at IT4Innovations.
+On these pages, we provide an overview of the profiling and debugging
+tools available on Anslem at IT4I.
+
+Intel debugger
+--------------
+
+The intel debugger version 13.0 is available, via module intel. The
+debugger works for applications compiled with C and C++ compiler and the
+ifort fortran 77/90/95 compiler. The debugger provides java GUI
+environment. Use [X
+display](https://docs.it4i.cz/anselm-cluster-documentation/software/debuggers/resolveuid/11e53ad0d2fd4c5187537f4baeedff33)
+for running the GUI.
+
+ $ module load intel
+ $ idb
+
+Read more at the [Intel
+Debugger](../intel-suite/intel-debugger.html) page.
+
+Allinea Forge (DDT/MAP)
+-----------------------
+
+Allinea DDT, is a commercial debugger primarily for debugging parallel
+MPI or OpenMP programs. It also has a support for GPU (CUDA) and Intel
+Xeon Phi accelerators. DDT provides all the standard debugging features
+(stack trace, breakpoints, watches, view variables, threads etc.) for
+every thread running as part of your program, or for every process -
+even if these processes are distributed across a cluster using an MPI
+implementation.
+
+ $ module load Forge
+ $ forge
+
+Read more at the [Allinea DDT](allinea-ddt.html) page.
+
+Allinea Performance Reports
+---------------------------
+
+Allinea Performance Reports characterize the performance of HPC
+application runs. After executing your application through the tool, a
+synthetic HTML report is generated automatically, containing information
+about several metrics along with clear behavior statements and hints to
+help you improve the efficiency of your runs. Our license is limited to
+64 MPI processes.
+
+ $ module load PerformanceReports/6.0
+ $ perf-report mpirun -n 64 ./my_application argument01 argument02
+
+Read more at the [Allinea Performance
+Reports](allinea-performance-reports.html) page.
+
+RougeWave Totalview
+-------------------
+
+TotalView is a source- and machine-level debugger for multi-process,
+multi-threaded programs. Its wide range of tools provides ways to
+analyze, organize, and test programs, making it easy to isolate and
+identify problems in individual threads and processes in programs of
+great complexity.
+
+ $ module load totalview
+ $ totalview
+
+Read more at the [Totalview](total-view.html) page.
+
+Vampir trace analyzer
+---------------------
+
+Vampir is a GUI trace analyzer for traces in OTF format.
+
+ $ module load Vampir/8.5.0
+ $ vampir
+
+Read more at
+the [Vampir](../../../salomon/software/debuggers/vampir.html) page.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/total-view.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/total-view.md
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+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/total-view.md
@@ -0,0 +1,165 @@
+Total View
+==========
+
+TotalView is a GUI-based source code multi-process, multi-thread
+debugger.
+
+License and Limitations for Anselm Users
+----------------------------------------
+
+On Anselm users can debug OpenMP or MPI code that runs up to 64 parallel
+processes. These limitation means that:
+
+Â Â Â 1 user can debug up 64 processes, or
+Â Â Â 32 users can debug 2 processes, etc.
+
+Debugging of GPU accelerated codes is also supported.
+
+You can check the status of the licenses here:
+
+ cat /apps/user/licenses/totalview_features_state.txt
+
+ # totalview
+ # -------------------------------------------------
+ # FEATUREÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â TOTALÂ Â USEDÂ AVAIL
+ # -------------------------------------------------
+ TotalView_Team                    64     0    64
+ Replay                            64     0    64
+ CUDAÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 64Â Â Â Â Â 0Â Â Â Â 64
+
+Compiling Code to run with TotalView
+------------------------------------
+
+### Modules
+
+Load all necessary modules to compile the code. For example:
+
+ module load intel
+
+ module load impi  ... or ... module load openmpi/X.X.X-icc
+
+Load the TotalView module:
+
+ module load totalview/8.12
+
+Compile the code:
+
+ mpicc -g -O0 -o test_debug test.c
+
+ mpif90 -g -O0 -o test_debug test.f
+
+### Compiler flags
+
+Before debugging, you need to compile your code with theses flags:
+
+-g** : Generates extra debugging information usable by GDB. -g3**
+includes even more debugging information. This option is available for
+GNU and INTEL C/C++ and Fortran compilers.
+
+-O0** : Suppress all optimizations.**
+
+Starting a Job with TotalView
+-----------------------------
+
+Be sure to log in with an X window forwarding enabled. This could mean
+using the -X in the ssh:Â
+
+ ssh -X username@anselm.it4i.cz
+
+Other options is to access login node using VNC. Please see the detailed
+information on how to use graphic user interface on Anselm
+[here](https://docs.it4i.cz/anselm-cluster-documentation/software/debuggers/resolveuid/11e53ad0d2fd4c5187537f4baeedff33#VNC).
+
+From the login node an interactive session with X windows forwarding (-X
+option) can be started by following command:
+
+ qsub -I -X -A NONE-0-0 -q qexp -lselect=1:ncpus=16:mpiprocs=16,walltime=01:00:00
+
+Then launch the debugger with the totalview command followed by the name
+of the executable to debug.
+
+### Debugging a serial code
+
+To debug a serial code use:
+
+ totalview test_debug
+
+### Debugging a parallel code - option 1
+
+To debug a parallel code compiled with >**OpenMPI** you need
+to setup your TotalView environment:Â
+
+Please note:** To be able to run parallel debugging procedure from the
+command line without stopping the debugger in the mpiexec source code
+you have to add the following function to your **~/.tvdrc** file:
+
+ proc mpi_auto_run_starter {loaded_id} {
+ Â Â Â set starter_programs {mpirun mpiexec orterun}
+ Â Â Â set executable_name [TV::symbol get $loaded_id full_pathname]
+ Â Â Â set file_component [file tail $executable_name]
+
+ Â Â Â if {[lsearch -exact $starter_programs $file_component] != -1} {
+ Â Â Â Â Â Â Â puts "*************************************"
+ Â Â Â Â Â Â Â puts "Automatically starting $file_component"
+ Â Â Â Â Â Â Â puts "*************************************"
+ Â Â Â Â Â Â Â dgo
+ Â Â Â }
+ }
+
+ # Append this function to TotalView's image load callbacks so that
+ # TotalView run this program automatically.
+
+ dlappend TV::image_load_callbacks mpi_auto_run_starter
+
+The source code of this function can be also found in
+
+ /apps/mpi/openmpi/intel/1.6.5/etc/openmpi-totalview.tcl
+
+You can also add only following line to you ~/.tvdrc file instead of
+the entire function:
+
+source /apps/mpi/openmpi/intel/1.6.5/etc/openmpi-totalview.tcl**
+
+You need to do this step only once.
+
+Now you can run the parallel debugger using:
+
+ mpirun -tv -n 5 ./test_debug
+
+When following dialog appears click on "Yes"
+
+
+
+At this point the main TotalView GUI window will appear and you can
+insert the breakpoints and start debugging:
+
+
+
+### Debugging a parallel code - option 2
+
+Other option to start new parallel debugging session from a command line
+is to let TotalView to execute mpirun by itself. In this case user has
+to specify a MPI implementation used to compile the source code.Â
+
+The following example shows how to start debugging session with Intel
+MPI:
+
+ module load intel/13.5.192 impi/4.1.1.036 totalview/8/13
+
+ totalview -mpi "Intel MPI-Hydra" -np 8 ./hello_debug_impi
+
+After running previous command you will see the same window as shown in
+the screenshot above.
+
+More information regarding the command line parameters of the TotalView
+can be found TotalView Reference Guide, Chapter 7: TotalView Command
+Syntax. Â
+
+Documentation
+-------------
+
+[1] The [TotalView
+documentation](http://www.roguewave.com/support/product-documentation/totalview-family.aspx#totalview)
+web page is a good resource for learning more about some of the advanced
+TotalView features.
+
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@@ -0,0 +1,292 @@
+Valgrind
+========
+
+Valgrind is a tool for memory debugging and profiling.
+
+About Valgrind
+--------------
+
+Valgrind is an open-source tool, used mainly for debuggig memory-related
+problems, such as memory leaks, use of uninitalized memory etc. in C/C++
+applications. The toolchain was however extended over time with more
+functionality, such as debugging of threaded applications, cache
+profiling, not limited only to C/C++.
+
+Valgind is an extremely useful tool for debugging memory errors such as
+[off-by-one](http://en.wikipedia.org/wiki/Off-by-one_error).
+Valgrind uses a virtual machine and dynamic recompilation of binary
+code, because of that, you can expect that programs being debugged by
+Valgrind run 5-100 times slower.
+
+The main tools available in Valgrind are :
+
+- **Memcheck**, the original, must used and default tool. Verifies
+ memory access in you program and can detect use of unitialized
+ memory, out of bounds memory access, memory leaks, double free, etc.
+- **Massif**, a heap profiler.
+- **Hellgrind** and **DRD** can detect race conditions in
+ multi-threaded applications.
+- **Cachegrind**, a cache profiler.
+- **Callgrind**, a callgraph analyzer.
+- For a full list and detailed documentation, please refer to the
+ [official Valgrind
+ documentation](http://valgrind.org/docs/).
+
+Installed versions
+------------------
+
+There are two versions of Valgrind available on Anselm.
+
+- >Version 3.6.0, installed by operating system vendor
+ in /usr/bin/valgrind.
+ >This version is available by default, without the need
+ to load any module. This version however does not provide additional
+ MPI support.
+- >Version 3.9.0 with support for Intel MPI, available in
+ [module](../../environment-and-modules.html)Â
+ valgrind/3.9.0-impi. After loading the
+ module, this version replaces the default valgrind.
+
+Usage
+-----
+
+Compile the application which you want to debug as usual. It is
+advisable to add compilation flags -g (to
+add debugging information to the binary so that you will see original
+source code lines in the output) and -O0
+(to disable compiler optimizations).Â
+
+For example, lets look at this C code, which has two problems :
+
+ #include <stdlib.h>
+
+ void f(void)
+ {
+ int* x = malloc(10 * sizeof(int));
+ x[10] = 0; // problem 1: heap block overrun
+ } // problem 2: memory leak -- x not freed
+
+ int main(void)
+ {
+ f();
+ return 0;
+ }
+
+Now, compile it with Intel compiler :
+
+ $ module add intel
+ $ icc -g valgrind-example.c -o valgrind-exampleÂ
+
+Now, lets run it with Valgrind. The syntax is :
+
+ valgrind [valgrind options] <your program
+binary> [your program options]
+
+If no Valgrind options are specified, Valgrind defaults to running
+Memcheck tool. Please refer to the Valgrind documentation for a full
+description of command line options.
+
+ $ valgrind ./valgrind-example
+ ==12652== Memcheck, a memory error detector
+ ==12652== Copyright (C) 2002-2013, and GNU GPL'd, by Julian Seward et al.
+ ==12652== Using Valgrind-3.9.0 and LibVEX; rerun with -h for copyright info
+ ==12652== Command: ./valgrind-example
+ ==12652==
+ ==12652== Invalid write of size 4
+ ==12652== at 0x40053E: f (valgrind-example.c:6)
+ ==12652== by 0x40054E: main (valgrind-example.c:11)
+ ==12652== Address 0x5861068 is 0 bytes after a block of size 40 alloc'd
+ ==12652== at 0x4C27AAA: malloc (vg_replace_malloc.c:291)
+ ==12652== by 0x400528: f (valgrind-example.c:5)
+ ==12652== by 0x40054E: main (valgrind-example.c:11)
+ ==12652==
+ ==12652==
+ ==12652== HEAP SUMMARY:
+ ==12652== in use at exit: 40 bytes in 1 blocks
+ ==12652== total heap usage: 1 allocs, 0 frees, 40 bytes allocated
+ ==12652==
+ ==12652== LEAK SUMMARY:
+ ==12652== definitely lost: 40 bytes in 1 blocks
+ ==12652== indirectly lost: 0 bytes in 0 blocks
+ ==12652== possibly lost: 0 bytes in 0 blocks
+ ==12652== still reachable: 0 bytes in 0 blocks
+ ==12652== suppressed: 0 bytes in 0 blocks
+ ==12652== Rerun with --leak-check=full to see details of leaked memory
+ ==12652==
+ ==12652== For counts of detected and suppressed errors, rerun with: -v
+ ==12652== ERROR SUMMARY: 1 errors from 1 contexts (suppressed: 6 from 6)
+
+In the output we can see that Valgrind has detected both errors - the
+off-by-one memory access at line 5 and a memory leak of 40 bytes. If we
+want a detailed analysis of the memory leak, we need to run Valgrind
+with --leak-check=full option :
+
+ $ valgrind --leak-check=full ./valgrind-example
+ ==23856== Memcheck, a memory error detector
+ ==23856== Copyright (C) 2002-2010, and GNU GPL'd, by Julian Seward et al.
+ ==23856== Using Valgrind-3.6.0 and LibVEX; rerun with -h for copyright info
+ ==23856== Command: ./valgrind-example
+ ==23856==
+ ==23856== Invalid write of size 4
+ ==23856== at 0x40067E: f (valgrind-example.c:6)
+ ==23856== by 0x40068E: main (valgrind-example.c:11)
+ ==23856== Address 0x66e7068 is 0 bytes after a block of size 40 alloc'd
+ ==23856== at 0x4C26FDE: malloc (vg_replace_malloc.c:236)
+ ==23856== by 0x400668: f (valgrind-example.c:5)
+ ==23856== by 0x40068E: main (valgrind-example.c:11)
+ ==23856==
+ ==23856==
+ ==23856== HEAP SUMMARY:
+ ==23856== in use at exit: 40 bytes in 1 blocks
+ ==23856== total heap usage: 1 allocs, 0 frees, 40 bytes allocated
+ ==23856==
+ ==23856== 40 bytes in 1 blocks are definitely lost in loss record 1 of 1
+ ==23856== at 0x4C26FDE: malloc (vg_replace_malloc.c:236)
+ ==23856== by 0x400668: f (valgrind-example.c:5)
+ ==23856== by 0x40068E: main (valgrind-example.c:11)
+ ==23856==
+ ==23856== LEAK SUMMARY:
+ ==23856== definitely lost: 40 bytes in 1 blocks
+ ==23856== indirectly lost: 0 bytes in 0 blocks
+ ==23856== possibly lost: 0 bytes in 0 blocks
+ ==23856== still reachable: 0 bytes in 0 blocks
+ ==23856== suppressed: 0 bytes in 0 blocks
+ ==23856==
+ ==23856== For counts of detected and suppressed errors, rerun with: -v
+ ==23856== ERROR SUMMARY: 2 errors from 2 contexts (suppressed: 6 from 6)
+
+Now we can see that the memory leak is due to the
+malloc() at line 6.
+
+Usage with MPI
+---------------------------
+
+Although Valgrind is not primarily a parallel debugger, it can be used
+to debug parallel applications as well. When launching your parallel
+applications, prepend the valgrind command. For example :
+
+ $ mpirun -np 4 valgrind myapplication
+
+The default version without MPI support will however report a large
+number of false errors in the MPI library, such as :
+
+ ==30166== Conditional jump or move depends on uninitialised value(s)
+ ==30166== at 0x4C287E8: strlen (mc_replace_strmem.c:282)
+ ==30166== by 0x55443BD: I_MPI_Processor_model_number (init_interface.c:427)
+ ==30166== by 0x55439E0: I_MPI_Processor_arch_code (init_interface.c:171)
+ ==30166== by 0x558D5AE: MPID_nem_impi_init_shm_configuration (mpid_nem_impi_extensions.c:1091)
+ ==30166== by 0x5598F4C: MPID_nem_init_ckpt (mpid_nem_init.c:566)
+ ==30166== by 0x5598B65: MPID_nem_init (mpid_nem_init.c:489)
+ ==30166== by 0x539BD75: MPIDI_CH3_Init (ch3_init.c:64)
+ ==30166== by 0x5578743: MPID_Init (mpid_init.c:193)
+ ==30166== by 0x554650A: MPIR_Init_thread (initthread.c:539)
+ ==30166== by 0x553369F: PMPI_Init (init.c:195)
+ ==30166== by 0x4008BD: main (valgrind-example-mpi.c:18)
+
+so it is better to use the MPI-enabled valgrind from module. The MPI
+version requires libraryÂ
+/apps/tools/valgrind/3.9.0/impi/lib/valgrind/libmpiwrap-amd64-linux.so,
+which must be included in the LD_PRELOAD
+environment variable.
+
+Lets look at this MPI example :
+
+ #include <stdlib.h>
+ #include <mpi.h>Â
+
+ int main(int argc, char *argv[])
+ {
+ Â Â Â Â Â int *data = malloc(sizeof(int)*99);
+
+ Â Â Â Â Â MPI_Init(&argc, &argv);
+ Â Â Â Â MPI_Bcast(data, 100, MPI_INT, 0, MPI_COMM_WORLD);
+ Â Â Â Â Â MPI_Finalize();Â
+
+ Â Â Â Â Â Â Â return 0;
+ }
+
+There are two errors - use of uninitialized memory and invalid length of
+the buffer. Lets debug it with valgrind :
+
+ $ module add intel impi
+ $ mpicc -g valgrind-example-mpi.c -o valgrind-example-mpi
+ $ module add valgrind/3.9.0-impi
+ $ mpirun -np 2 -env LD_PRELOAD /apps/tools/valgrind/3.9.0/impi/lib/valgrind/libmpiwrap-amd64-linux.so valgrind ./valgrind-example-mpi
+
+Prints this output : (note that there is output printed for every
+launched MPI process)
+
+ ==31318== Memcheck, a memory error detector
+ ==31318== Copyright (C) 2002-2013, and GNU GPL'd, by Julian Seward et al.
+ ==31318== Using Valgrind-3.9.0 and LibVEX; rerun with -h for copyright info
+ ==31318== Command: ./valgrind-example-mpi
+ ==31318==
+ ==31319== Memcheck, a memory error detector
+ ==31319== Copyright (C) 2002-2013, and GNU GPL'd, by Julian Seward et al.
+ ==31319== Using Valgrind-3.9.0 and LibVEX; rerun with -h for copyright info
+ ==31319== Command: ./valgrind-example-mpi
+ ==31319==
+ valgrind MPI wrappers 31319: Active for pid 31319
+ valgrind MPI wrappers 31319: Try MPIWRAP_DEBUG=help for possible options
+ valgrind MPI wrappers 31318: Active for pid 31318
+ valgrind MPI wrappers 31318: Try MPIWRAP_DEBUG=help for possible options
+ ==31319== Unaddressable byte(s) found during client check request
+ ==31319== at 0x4E35974: check_mem_is_addressable_untyped (libmpiwrap.c:960)
+ ==31319== by 0x4E5D0FE: PMPI_Bcast (libmpiwrap.c:908)
+ ==31319== by 0x400911: main (valgrind-example-mpi.c:20)
+ ==31319== Address 0x69291cc is 0 bytes after a block of size 396 alloc'd
+ ==31319== at 0x4C27AAA: malloc (vg_replace_malloc.c:291)
+ ==31319== by 0x4007BC: main (valgrind-example-mpi.c:8)
+ ==31319==
+ ==31318== Uninitialised byte(s) found during client check request
+ ==31318== at 0x4E3591D: check_mem_is_defined_untyped (libmpiwrap.c:952)
+ ==31318== by 0x4E5D06D: PMPI_Bcast (libmpiwrap.c:908)
+ ==31318== by 0x400911: main (valgrind-example-mpi.c:20)
+ ==31318== Address 0x6929040 is 0 bytes inside a block of size 396 alloc'd
+ ==31318== at 0x4C27AAA: malloc (vg_replace_malloc.c:291)
+ ==31318== by 0x4007BC: main (valgrind-example-mpi.c:8)
+ ==31318==
+ ==31318== Unaddressable byte(s) found during client check request
+ ==31318== at 0x4E3591D: check_mem_is_defined_untyped (libmpiwrap.c:952)
+ ==31318== by 0x4E5D06D: PMPI_Bcast (libmpiwrap.c:908)
+ ==31318== by 0x400911: main (valgrind-example-mpi.c:20)
+ ==31318== Address 0x69291cc is 0 bytes after a block of size 396 alloc'd
+ ==31318== at 0x4C27AAA: malloc (vg_replace_malloc.c:291)
+ ==31318== by 0x4007BC: main (valgrind-example-mpi.c:8)
+ ==31318==
+ ==31318==
+ ==31318== HEAP SUMMARY:
+ ==31318== in use at exit: 3,172 bytes in 67 blocks
+ ==31318== total heap usage: 191 allocs, 124 frees, 81,203 bytes allocated
+ ==31318==
+ ==31319==
+ ==31319== HEAP SUMMARY:
+ ==31319== in use at exit: 3,172 bytes in 67 blocks
+ ==31319== total heap usage: 175 allocs, 108 frees, 48,435 bytes allocated
+ ==31319==
+ ==31318== LEAK SUMMARY:
+ ==31318== definitely lost: 408 bytes in 3 blocks
+ ==31318== indirectly lost: 256 bytes in 1 blocks
+ ==31318== possibly lost: 0 bytes in 0 blocks
+ ==31318== still reachable: 2,508 bytes in 63 blocks
+ ==31318== suppressed: 0 bytes in 0 blocks
+ ==31318== Rerun with --leak-check=full to see details of leaked memory
+ ==31318==
+ ==31318== For counts of detected and suppressed errors, rerun with: -v
+ ==31318== Use --track-origins=yes to see where uninitialised values come from
+ ==31318== ERROR SUMMARY: 2 errors from 2 contexts (suppressed: 4 from 4)
+ ==31319== LEAK SUMMARY:
+ ==31319== definitely lost: 408 bytes in 3 blocks
+ ==31319== indirectly lost: 256 bytes in 1 blocks
+ ==31319== possibly lost: 0 bytes in 0 blocks
+ ==31319== still reachable: 2,508 bytes in 63 blocks
+ ==31319== suppressed: 0 bytes in 0 blocks
+ ==31319== Rerun with --leak-check=full to see details of leaked memory
+ ==31319==
+ ==31319== For counts of detected and suppressed errors, rerun with: -v
+ ==31319== ERROR SUMMARY: 1 errors from 1 contexts (suppressed: 4 from 4)
+
+We can see that Valgrind has reported use of unitialised memory on the
+master process (which reads the array to be broadcasted) and use of
+unaddresable memory on both processes.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/vampir.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/vampir.md
new file mode 100644
index 0000000000000000000000000000000000000000..25fb484c6bf776ca15594007823269357514b8d3
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/vampir.md
@@ -0,0 +1,33 @@
+Vampir
+======
+
+Vampir is a commercial trace analysis and visualisation tool. It can
+work with traces in OTF and OTF2 formats. It does not have the
+functionality to collect traces, you need to use a trace collection tool
+(such
+as [Score-P](../../../salomon/software/debuggers/score-p.html))
+first to collect the traces.
+
+
+-------------------------------------
+
+Installed versions
+------------------
+
+Version 8.5.0 is currently installed as moduleÂ
+Vampir/8.5.0Â :
+
+ $ module load Vampir/8.5.0
+ $ vampir &
+
+User manual
+-----------
+
+You can find the detailed user manual in PDF format inÂ
+$EBROOTVAMPIR/doc/vampir-manual.pdf
+
+References
+----------
+
+1. <https://www.vampir.eu>
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/vtune-amplifier.png b/converted/docs.it4i.cz/anselm-cluster-documentation/software/debuggers/vtune-amplifier.png
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diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/gpi2.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/gpi2.md
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index 0000000000000000000000000000000000000000..79cf34786cbae1912747eb9dc563d189cc9c8df7
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/gpi2.md
@@ -0,0 +1,182 @@
+GPI-2
+=====
+
+A library that implements the GASPI specification
+
+
+
+Introduction
+------------
+
+Programming Next Generation Supercomputers: GPI-2 is an API library for
+asynchronous interprocess, cross-node communication. It provides a
+flexible, scalable and fault tolerant interface for parallel
+applications.
+
+The GPI-2 library
+([www.gpi-site.com/gpi2/](http://www.gpi-site.com/gpi2/))
+implements the GASPI specification (Global Address Space Programming
+Interface,
+[www.gaspi.de](http://www.gaspi.de/en/project.html)).
+GASPI is a Partitioned Global Address Space (PGAS) API. It aims at
+scalable, flexible and failure tolerant computing in massively parallel
+environments.
+
+Modules
+-------
+
+The GPI-2, version 1.0.2 is available on Anselm via module gpi2:
+
+ $ module load gpi2
+
+The module sets up environment variables, required for linking and
+running GPI-2 enabled applications. This particular command loads the
+default module, which is gpi2/1.0.2
+
+Linking
+-------
+
+Link with -lGPI2 -libverbs
+
+Load the gpi2 module. Link using **-lGPI2** and *** **-libverbs**
+switches to link your code against GPI-2. The GPI-2 requires the OFED
+infinband communication library ibverbs.
+
+### Compiling and linking with Intel compilers
+
+ $ module load intel
+ $ module load gpi2
+ $ icc myprog.c -o myprog.x -Wl,-rpath=$LIBRARY_PATH -lGPI2 -libverbs
+
+### Compiling and linking with GNU compilers
+
+ $ module load gcc
+ $ module load gpi2
+ $ gcc myprog.c -o myprog.x -Wl,-rpath=$LIBRARY_PATH -lGPI2 -libverbs
+
+Running the GPI-2 codes
+-----------------------
+
+gaspi_run
+
+gaspi_run starts the GPI-2 application
+
+The gaspi_run utility is used to start and run GPI-2 applications:
+
+ $ gaspi_run -m machinefile ./myprog.x
+
+A machine file (**machinefile**) with the hostnames of nodes where the
+application will run, must be provided. The*** machinefile lists all
+nodes on which to run, one entry per node per process. This file may be
+hand created or obtained from standard $PBS_NODEFILE:
+
+ $ cut -f1 -d"." $PBS_NODEFILE > machinefile
+
+machinefile:
+
+ cn79
+ cn80
+
+This machinefile will run 2 GPI-2 processes, one on node cn79 other on
+node cn80.
+
+machinefle:
+
+ cn79
+ cn79
+ cn80
+ cn80
+
+This machinefile will run 4 GPI-2 processes, 2 on node cn79 o 2 on node
+cn80.
+
+Use the **mpiprocs** to control how many GPI-2 processes will run per
+node
+
+Example:
+
+ $ qsub -A OPEN-0-0 -q qexp -l select=2:ncpus=16:mpiprocs=16 -I
+
+This example will produce $PBS_NODEFILE with 16 entries per node.
+
+### gaspi_logger
+
+gaspi_logger views the output form GPI-2 application ranks
+
+The gaspi_logger utility is used to view the output from all nodes
+except the master node (rank 0). The gaspi_logger is started, on
+another session, on the master node - the node where the gaspi_run is
+executed. The output of the application, when called with
+gaspi_printf(), will be redirected to the gaspi_logger. Other I/O
+routines (e.g. printf) will not.
+
+Example
+-------
+
+Following is an example GPI-2 enabled code:
+
+ #include <GASPI.h>
+ #include <stdlib.h>
+
+ void success_or_exit ( const char* file, const int line, const int ec)
+ {
+ if (ec != GASPI_SUCCESS)
+ {
+ gaspi_printf ("Assertion failed in %s[%i]:%dn", file, line, ec);
+ exit (1);
+ }
+ }
+
+ #define ASSERT(ec) success_or_exit (__FILE__, __LINE__, ec);
+
+ int main(int argc, char *argv[])
+ {
+ gaspi_rank_t rank, num;
+ gaspi_return_t ret;
+
+ /* Initialize GPI-2 */
+ ASSERT( gaspi_proc_init(GASPI_BLOCK) );
+
+ /* Get ranks information */
+ ASSERT( gaspi_proc_rank(&rank) );
+ ASSERT( gaspi_proc_num(&num) );
+
+ gaspi_printf("Hello from rank %d of %dn",
+ rank, num);
+
+ /* Terminate */
+ ASSERT( gaspi_proc_term(GASPI_BLOCK) );
+
+ return 0;
+ }
+
+Load modules and compile:
+
+ $ module load gcc gpi2
+ $ gcc helloworld_gpi.c -o helloworld_gpi.x -Wl,-rpath=$LIBRARY_PATH -lGPI2 -libverbs
+
+Submit the job and run the GPI-2 application
+
+ $ qsub -q qexp -l select=2:ncpus=1:mpiprocs=1,place=scatter,walltime=00:05:00 -I
+ qsub: waiting for job 171247.dm2 to start
+ qsub: job 171247.dm2 ready
+
+ cn79 $ module load gpi2
+ cn79 $ cut -f1 -d"." $PBS_NODEFILE > machinefile
+ cn79 $ gaspi_run -m machinefile ./helloworld_gpi.x
+ Hello from rank 0 of 2
+
+At the same time, in another session, you may start the gaspi logger:
+
+ $ ssh cn79
+ cn79 $ gaspi_logger
+ GASPI Logger (v1.1)
+ [cn80:0] Hello from rank 1 of 2
+
+In this example, we compile the helloworld_gpi.c code using the **gnu
+compiler**Â (gcc) and link it to the GPI-2 and ibverbs library. The
+library search path is compiled in. For execution, we use the qexp
+queue, 2 nodes 1 core each. The GPI module must be loaded on the master
+compute node (in this example the cn79), gaspi_logger is used from
+different session to view the output of the second process.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite.md
new file mode 100644
index 0000000000000000000000000000000000000000..7c41a4badd18bd8868a96cf81a5bfd780f2daef5
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite.md
@@ -0,0 +1,93 @@
+Intel Parallel Studio
+=====================
+
+
+
+The Anselm cluster provides following elements of the Intel Parallel
+Studio XE
+
+ Intel Parallel Studio XE
+ -------------------------------------------------
+ Intel Compilers
+ Intel Debugger
+ Intel MKL Library
+ Intel Integrated Performance Primitives Library
+ Intel Threading Building Blocks Library
+
+Intel compilers
+---------------
+
+The Intel compilers version 13.1.3 are available, via module intel. The
+compilers include the icc C and C++ compiler and the ifort fortran
+77/90/95 compiler.
+
+ $ module load intel
+ $ icc -v
+ $ ifort -v
+
+Read more at the [Intel
+Compilers](intel-suite/intel-compilers.html) page.
+
+Intel debugger
+--------------
+
+Â The intel debugger version 13.0 is available, via module intel. The
+debugger works for applications compiled with C and C++ compiler and the
+ifort fortran 77/90/95 compiler. The debugger provides java GUI
+environment. Use [X
+display](https://docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/resolveuid/11e53ad0d2fd4c5187537f4baeedff33)
+for running the GUI.
+
+ $ module load intel
+ $ idb
+
+Read more at the [Intel
+Debugger](intel-suite/intel-debugger.html) page.
+
+Intel Math Kernel Library
+-------------------------
+
+Intel Math Kernel Library (Intel MKL) is a library of math kernel
+subroutines, extensively threaded and optimized for maximum performance.
+Intel MKL unites and provides these basic components: BLAS, LAPACK,
+ScaLapack, PARDISO, FFT, VML, VSL, Data fitting, Feast Eigensolver and
+many more.
+
+ $ module load mkl
+
+Read more at the [Intel MKL](intel-suite/intel-mkl.html)
+page.
+
+Intel Integrated Performance Primitives
+---------------------------------------
+
+Intel Integrated Performance Primitives, version 7.1.1, compiled for AVX
+is available, via module ipp. The IPP is a library of highly optimized
+algorithmic building blocks for media and data applications. This
+includes signal, image and frame processing algorithms, such as FFT,
+FIR, Convolution, Optical Flow, Hough transform, Sum, MinMax and many
+more.
+
+ $ module load ipp
+
+Read more at the [Intel
+IPP](intel-suite/intel-integrated-performance-primitives.html)
+page.
+
+Intel Threading Building Blocks
+-------------------------------
+
+Intel Threading Building Blocks (Intel TBB) is a library that supports
+scalable parallel programming using standard ISO C++ code. It does not
+require special languages or compilers. It is designed to promote
+scalable data parallel programming. Additionally, it fully supports
+nested parallelism, so you can build larger parallel components from
+smaller parallel components. To use the library, you specify tasks, not
+threads, and let the library map tasks onto threads in an efficient
+manner.
+
+ $ module load tbb
+
+Read more at the [Intel TBB](intel-suite/intel-tbb.html)
+page.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-compilers.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-compilers.md
new file mode 100644
index 0000000000000000000000000000000000000000..14ce867f6134899a2dc91b51f5b932d6b752a424
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-compilers.md
@@ -0,0 +1,66 @@
+Intel Compilers
+===============
+
+
+
+The Intel compilers version 13.1.1 are available, via module intel. The
+compilers include the icc C and C++ compiler and the ifort fortran
+77/90/95 compiler.
+
+ $ module load intel
+ $ icc -v
+ $ ifort -v
+
+The intel compilers provide for vectorization of the code, via the AVX
+instructions and support threading parallelization via OpenMP
+
+For maximum performance on the Anselm cluster, compile your programs
+using the AVX instructions, with reporting where the vectorization was
+used. We recommend following compilation options for high performance
+
+ $ icc -ipo -O3 -vec -xAVX -vec-report1 myprog.c mysubroutines.c -o myprog.x
+ $ ifort -ipo -O3 -vec -xAVX -vec-report1 myprog.f mysubroutines.f -o myprog.x
+
+In this example, we compile the program enabling interprocedural
+optimizations between source files (-ipo), aggresive loop optimizations
+(-O3) and vectorization (-vec -xAVX)
+
+The compiler recognizes the omp, simd, vector and ivdep pragmas for
+OpenMP parallelization and AVX vectorization. Enable the OpenMP
+parallelization by the **-openmp** compiler switch.
+
+ $ icc -ipo -O3 -vec -xAVX -vec-report1 -openmp myprog.c mysubroutines.c -o myprog.x
+ $ ifort -ipo -O3 -vec -xAVX -vec-report1 -openmp myprog.f mysubroutines.f -o myprog.x
+
+Read more at
+<http://software.intel.com/sites/products/documentation/doclib/stdxe/2013/composerxe/compiler/cpp-lin/index.htm>
+
+Sandy Bridge/Haswell binary compatibility
+-----------------------------------------
+
+Anselm nodes are currently equipped with Sandy Bridge CPUs, while
+Salomon will use Haswell architecture. >The new processors are
+backward compatible with the Sandy Bridge nodes, so all programs that
+ran on the Sandy Bridge processors, should also run on the new Haswell
+nodes. >To get optimal performance out of the Haswell
+processors a program should make use of the special >AVX2
+instructions for this processor. One can do this by recompiling codes
+with the compiler flags >designated to invoke these
+instructions. For the Intel compiler suite, there are two ways of
+doing >this:
+
+- >Using compiler flag (both for Fortran and C):
+ -xCORE-AVX2. This will create a
+ binary class="s1">with AVX2 instructions, specifically
+ for the Haswell processors. Note that the
+ executable >will not run on Sandy Bridge nodes.
+- >Using compiler flags (both for Fortran and C):
+ -xAVX -axCORE-AVX2. This
+ will >generate multiple, feature specific auto-dispatch
+ code paths for Intel® processors, if there is >a
+ performance benefit. So this binary will run both on Sandy Bridge
+ and Haswell >processors. During runtime it will be
+ decided which path to follow, dependent on
+ which >processor you are running on. In general this
+ will result in larger binaries.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-debugger.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-debugger.md
new file mode 100644
index 0000000000000000000000000000000000000000..35ba0de033b074f26a5a2b1a455f3b3245e012c4
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-debugger.md
@@ -0,0 +1,97 @@
+Intel Debugger
+==============
+
+
+
+Debugging serial applications
+-----------------------------
+
+Â The intel debugger version 13.0 is available, via module intel. The
+debugger works for applications compiled with C and C++ compiler and the
+ifort fortran 77/90/95 compiler. The debugger provides java GUI
+environment. Use [X
+display](https://docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/resolveuid/11e53ad0d2fd4c5187537f4baeedff33)
+for running the GUI.
+
+ $ module load intel
+ $ idb
+
+The debugger may run in text mode. To debug in text mode, use
+
+ $ idbc
+
+To debug on the compute nodes, module intel must be loaded.
+The GUI on compute nodes may be accessed using the same way as in [the
+GUI
+section](https://docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/resolveuid/11e53ad0d2fd4c5187537f4baeedff33)
+
+Example:
+
+ $ qsub -q qexp -l select=1:ncpus=16 -X -I
+ qsub: waiting for job 19654.srv11 to start
+ qsub: job 19654.srv11 ready
+
+ $ module load intel
+ $ module load java
+ $ icc -O0 -g myprog.c -o myprog.x
+ $ idb ./myprog.x
+
+In this example, we allocate 1 full compute node, compile program
+myprog.c with debugging options -O0 -g and run the idb debugger
+interactively on the myprog.x executable. The GUI access is via X11 port
+forwarding provided by the PBS workload manager.
+
+Debugging parallel applications
+-------------------------------
+
+Intel debugger is capable of debugging multithreaded and MPI parallel
+programs as well.
+
+### Small number of MPI ranks
+
+For debugging small number of MPI ranks, you may execute and debug each
+rank in separate xterm terminal (do not forget the [X
+display](https://docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/resolveuid/11e53ad0d2fd4c5187537f4baeedff33)).
+Using Intel MPI, this may be done in following way:
+
+ $ qsub -q qexp -l select=2:ncpus=16 -X -I
+ qsub: waiting for job 19654.srv11 to start
+ qsub: job 19655.srv11 ready
+
+ $ module load intel impi
+ $ mpirun -ppn 1 -hostfile $PBS_NODEFILE --enable-x xterm -e idbc ./mympiprog.x
+
+In this example, we allocate 2 full compute node, run xterm on each node
+and start idb debugger in command line mode, debugging two ranks of
+mympiprog.x application. The xterm will pop up for each rank, with idb
+prompt ready. The example is not limited to use of Intel MPI
+
+### Large number of MPI ranks
+
+Run the idb debugger from within the MPI debug option. This will cause
+the debugger to bind to all ranks and provide aggregated outputs across
+the ranks, pausing execution automatically just after startup. You may
+then set break points and step the execution manually. Using Intel MPI:
+
+ $ qsub -q qexp -l select=2:ncpus=16 -X -I
+ qsub: waiting for job 19654.srv11 to start
+ qsub: job 19655.srv11 ready
+
+ $ module load intel impi
+ $ mpirun -n 32 -idb ./mympiprog.x
+
+### Debugging multithreaded application
+
+Run the idb debugger in GUI mode. The menu Parallel contains number of
+tools for debugging multiple threads. One of the most useful tools is
+the **Serialize Execution** tool, which serializes execution of
+concurrent threads for easy orientation and identification of
+concurrency related bugs.
+
+Further information
+-------------------
+
+Exhaustive manual on idb features and usage is published at Intel
+website,
+<http://software.intel.com/sites/products/documentation/doclib/stdxe/2013/composerxe/debugger/user_guide/index.htm>
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-integrated-performance-primitives.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-integrated-performance-primitives.md
new file mode 100644
index 0000000000000000000000000000000000000000..5cef1f8f67d5d7759953e5579300adeff1c21af1
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-integrated-performance-primitives.md
@@ -0,0 +1,94 @@
+Intel IPP
+=========
+
+
+
+Intel Integrated Performance Primitives
+---------------------------------------
+
+Intel Integrated Performance Primitives, version 7.1.1, compiled for AVX
+vector instructions is available, via module ipp. The IPP is a very rich
+library of highly optimized algorithmic building blocks for media and
+data applications. This includes signal, image and frame processing
+algorithms, such as FFT, FIR, Convolution, Optical Flow, Hough
+transform, Sum, MinMax, as well as cryptographic functions, linear
+algebra functions and many more.
+
+Check out IPP before implementing own math functions for data
+processing, it is likely already there.
+
+ $ module load ipp
+
+The module sets up environment variables, required for linking and
+running ipp enabled applications.
+
+IPP example
+-----------
+
+ #include "ipp.h"
+ #include <stdio.h>
+ int main(int argc, char* argv[])
+ {
+ const IppLibraryVersion *lib;
+ Ipp64u fm;
+ IppStatus status;
+
+ status= ippInit(); //IPP initialization with the best optimization layer
+ if( status != ippStsNoErr ) {
+ printf("IppInit() Error:n");
+ printf("%sn", ippGetStatusString(status) );
+ return -1;
+ }
+
+ //Get version info
+ lib = ippiGetLibVersion();
+ printf("%s %sn", lib->Name, lib->Version);
+
+ //Get CPU features enabled with selected library level
+ fm=ippGetEnabledCpuFeatures();
+ printf("SSE :%cn",(fm>1)&1?'Y':'N');
+ printf("SSE2 :%cn",(fm>2)&1?'Y':'N');
+ printf("SSE3 :%cn",(fm>3)&1?'Y':'N');
+ printf("SSSE3 :%cn",(fm>4)&1?'Y':'N');
+ printf("SSE41 :%cn",(fm>6)&1?'Y':'N');
+ printf("SSE42 :%cn",(fm>7)&1?'Y':'N');
+ printf("AVX :%cn",(fm>8)&1 ?'Y':'N');
+ printf("AVX2 :%cn", (fm>15)&1 ?'Y':'N' );
+ printf("----------n");
+ printf("OS Enabled AVX :%cn", (fm>9)&1 ?'Y':'N');
+ printf("AES :%cn", (fm>10)&1?'Y':'N');
+ printf("CLMUL :%cn", (fm>11)&1?'Y':'N');
+ printf("RDRAND :%cn", (fm>13)&1?'Y':'N');
+ printf("F16C :%cn", (fm>14)&1?'Y':'N');
+
+ return 0;
+ }
+
+Â Compile above example, using any compiler and the ipp module.
+
+ $ module load intel
+ $ module load ipp
+
+ $ icc testipp.c -o testipp.x -lippi -lipps -lippcore
+
+You will need the ipp module loaded to run the ipp enabled executable.
+This may be avoided, by compiling library search paths into the
+executable
+
+ $ module load intel
+ $ module load ipp
+
+ $ icc testipp.c -o testipp.x -Wl,-rpath=$LIBRARY_PATH -lippi -lipps -lippcore
+
+Code samples and documentation
+------------------------------
+
+Intel provides number of [Code Samples for
+IPP](https://software.intel.com/en-us/articles/code-samples-for-intel-integrated-performance-primitives-library),
+illustrating use of IPP.
+
+Read full documentation on IPP [on Intel
+website,](http://software.intel.com/sites/products/search/search.php?q=&x=15&y=6&product=ipp&version=7.1&docos=lin)
+in particular the [IPP Reference
+manual.](http://software.intel.com/sites/products/documentation/doclib/ipp_sa/71/ipp_manual/index.htm)
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-mkl.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-mkl.md
new file mode 100644
index 0000000000000000000000000000000000000000..935f78fcce4c90447fcd259318490f69f03fced7
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-mkl.md
@@ -0,0 +1,190 @@
+Intel MKL
+=========
+
+
+
+Intel Math Kernel Library
+-------------------------
+
+Intel Math Kernel Library (Intel MKL) is a library of math kernel
+subroutines, extensively threaded and optimized for maximum performance.
+Intel MKL provides these basic math kernels:
+
+-
+
+
+
+ BLAS (level 1, 2, and 3) and LAPACK linear algebra routines,
+ offering vector, vector-matrix, and matrix-matrix operations.
+-
+
+
+
+ The PARDISO direct sparse solver, an iterative sparse solver,
+ and supporting sparse BLAS (level 1, 2, and 3) routines for solving
+ sparse systems of equations.
+-
+
+
+
+ ScaLAPACK distributed processing linear algebra routines for
+ Linux* and Windows* operating systems, as well as the Basic Linear
+ Algebra Communications Subprograms (BLACS) and the Parallel Basic
+ Linear Algebra Subprograms (PBLAS).
+-
+
+
+
+ Fast Fourier transform (FFT) functions in one, two, or three
+ dimensions with support for mixed radices (not limited to sizes that
+ are powers of 2), as well as distributed versions of
+ these functions.
+-
+
+
+
+ Vector Math Library (VML) routines for optimized mathematical
+ operations on vectors.
+-
+
+
+
+ Vector Statistical Library (VSL) routines, which offer
+ high-performance vectorized random number generators (RNG) for
+ several probability distributions, convolution and correlation
+ routines, and summary statistics functions.
+-
+
+
+
+ Data Fitting Library, which provides capabilities for
+ spline-based approximation of functions, derivatives and integrals
+ of functions, and search.
+- Extended Eigensolver, a shared memory version of an eigensolver
+ based on the Feast Eigenvalue Solver.
+
+For details see the [Intel MKL Reference
+Manual](http://software.intel.com/sites/products/documentation/doclib/mkl_sa/11/mklman/index.htm).
+
+Intel MKL version 13.5.192 is available on Anselm
+
+ $ module load mkl
+
+The module sets up environment variables, required for linking and
+running mkl enabled applications. The most important variables are the
+$MKLROOT, $MKL_INC_DIR, $MKL_LIB_DIR and $MKL_EXAMPLES
+
+The MKL library may be linked using any compiler.
+With intel compiler use -mkl option to link default threaded MKL.
+
+### Interfaces
+
+The MKL library provides number of interfaces. The fundamental once are
+the LP64 and ILP64. The Intel MKL ILP64 libraries use the 64-bit integer
+type (necessary for indexing large arrays, with more than 231^-1
+elements), whereas the LP64 libraries index arrays with the 32-bit
+integer type.
+
+ |Interface|Integer type|
+ ----- |---|---|-------------------------------------
+ |LP64|32-bit, int, integer(kind=4), MPI_INT|
+ ILP64 64-bit, long int, integer(kind=8), MPI_INT64
+
+### Linking
+
+Linking MKL libraries may be complex. Intel [mkl link line
+advisor](http://software.intel.com/en-us/articles/intel-mkl-link-line-advisor)
+helps. See also [examples](intel-mkl.html#examples) below.
+
+You will need the mkl module loaded to run the mkl enabled executable.
+This may be avoided, by compiling library search paths into the
+executable. Include rpath on the compile line:
+
+ $ icc .... -Wl,-rpath=$LIBRARY_PATH ...
+
+### Threading
+
+Advantage in using the MKL library is that it brings threaded
+parallelization to applications that are otherwise not parallel.
+
+For this to work, the application must link the threaded MKL library
+(default). Number and behaviour of MKL threads may be controlled via the
+OpenMP environment variables, such as OMP_NUM_THREADS and
+KMP_AFFINITY. MKL_NUM_THREADS takes precedence over OMP_NUM_THREADS
+
+ $ export OMP_NUM_THREADS=16
+ $ export KMP_AFFINITY=granularity=fine,compact,1,0
+
+The application will run with 16 threads with affinity optimized for
+fine grain parallelization.
+
+Examples
+------------
+
+Number of examples, demonstrating use of the MKL library and its linking
+is available on Anselm, in the $MKL_EXAMPLES directory. In the
+examples below, we demonstrate linking MKL to Intel and GNU compiled
+program for multi-threaded matrix multiplication.
+
+### Working with examples
+
+ $ module load intel
+ $ module load mkl
+ $ cp -a $MKL_EXAMPLES/cblas /tmp/
+ $ cd /tmp/cblas
+
+ $ make sointel64 function=cblas_dgemm
+
+In this example, we compile, link and run the cblas_dgemm example,
+demonstrating use of MKL example suite installed on Anselm.
+
+### Example: MKL and Intel compiler
+
+ $ module load intel
+ $ module load mkl
+ $ cp -a $MKL_EXAMPLES/cblas /tmp/
+ $ cd /tmp/cblas
+ $
+ $ icc -w source/cblas_dgemmx.c source/common_func.c -mkl -o cblas_dgemmx.x
+ $ ./cblas_dgemmx.x data/cblas_dgemmx.d
+
+In this example, we compile, link and run the cblas_dgemm example,
+demonstrating use of MKL with icc -mkl option. Using the -mkl option is
+equivalent to:
+
+ $ icc -w source/cblas_dgemmx.c source/common_func.c -o cblas_dgemmx.x
+ -I$MKL_INC_DIR -L$MKL_LIB_DIR -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -liomp5
+
+In this example, we compile and link the cblas_dgemm example, using
+LP64 interface to threaded MKL and Intel OMP threads implementation.
+
+### Example: MKL and GNU compiler
+
+ $ module load gcc
+ $ module load mkl
+ $ cp -a $MKL_EXAMPLES/cblas /tmp/
+ $ cd /tmp/cblas
+
+ $ gcc -w source/cblas_dgemmx.c source/common_func.c -o cblas_dgemmx.x
+ -lmkl_intel_lp64 -lmkl_gnu_thread -lmkl_core -lgomp -lm
+
+ $ ./cblas_dgemmx.x data/cblas_dgemmx.d
+
+In this example, we compile, link and run the cblas_dgemm example,
+using LP64 interface to threaded MKL and gnu OMP threads implementation.
+
+MKL and MIC accelerators
+------------------------
+
+The MKL is capable to automatically offload the computations o the MIC
+accelerator. See section [Intel Xeon
+Phi](../intel-xeon-phi.html) for details.
+
+Further reading
+---------------
+
+Read more on [Intel
+website](http://software.intel.com/en-us/intel-mkl), in
+particular the [MKL users
+guide](https://software.intel.com/en-us/intel-mkl/documentation/linux).
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-parallel-studio-introduction.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-parallel-studio-introduction.md
new file mode 100644
index 0000000000000000000000000000000000000000..26077232e61fd20ffac4312e58be70dcc12c7934
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-parallel-studio-introduction.md
@@ -0,0 +1,90 @@
+Intel Parallel Studio
+=====================
+
+
+
+The Anselm cluster provides following elements of the Intel Parallel
+Studio XE
+
+ Intel Parallel Studio XE
+ -------------------------------------------------
+ Intel Compilers
+ Intel Debugger
+ Intel MKL Library
+ Intel Integrated Performance Primitives Library
+ Intel Threading Building Blocks Library
+
+Intel compilers
+---------------
+
+The Intel compilers version 13.1.3 are available, via module intel. The
+compilers include the icc C and C++ compiler and the ifort fortran
+77/90/95 compiler.
+
+ $ module load intel
+ $ icc -v
+ $ ifort -v
+
+Read more at the [Intel Compilers](intel-compilers.html)
+page.
+
+Intel debugger
+--------------
+
+Â The intel debugger version 13.0 is available, via module intel. The
+debugger works for applications compiled with C and C++ compiler and the
+ifort fortran 77/90/95 compiler. The debugger provides java GUI
+environment. Use [X
+display](https://docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/resolveuid/11e53ad0d2fd4c5187537f4baeedff33)
+for running the GUI.
+
+ $ module load intel
+ $ idb
+
+Read more at the [Intel Debugger](intel-debugger.html)
+page.
+
+Intel Math Kernel Library
+-------------------------
+
+Intel Math Kernel Library (Intel MKL) is a library of math kernel
+subroutines, extensively threaded and optimized for maximum performance.
+Intel MKL unites and provides these basic components: BLAS, LAPACK,
+ScaLapack, PARDISO, FFT, VML, VSL, Data fitting, Feast Eigensolver and
+many more.
+
+ $ module load mkl
+
+Read more at the [Intel MKL](intel-mkl.html) page.
+
+Intel Integrated Performance Primitives
+---------------------------------------
+
+Intel Integrated Performance Primitives, version 7.1.1, compiled for AVX
+is available, via module ipp. The IPP is a library of highly optimized
+algorithmic building blocks for media and data applications. This
+includes signal, image and frame processing algorithms, such as FFT,
+FIR, Convolution, Optical Flow, Hough transform, Sum, MinMax and many
+more.
+
+ $ module load ipp
+
+Read more at the [Intel
+IPP](intel-integrated-performance-primitives.html) page.
+
+Intel Threading Building Blocks
+-------------------------------
+
+Intel Threading Building Blocks (Intel TBB) is a library that supports
+scalable parallel programming using standard ISO C++ code. It does not
+require special languages or compilers. It is designed to promote
+scalable data parallel programming. Additionally, it fully supports
+nested parallelism, so you can build larger parallel components from
+smaller parallel components. To use the library, you specify tasks, not
+threads, and let the library map tasks onto threads in an efficient
+manner.
+
+ $ module load tbb
+
+Read more at the [Intel TBB](intel-tbb.html) page.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-tbb.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-tbb.md
new file mode 100644
index 0000000000000000000000000000000000000000..29c0fa654de6a6bfe8bf4f34b0ba73c756b28a5b
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/intel-suite/intel-tbb.md
@@ -0,0 +1,54 @@
+Intel TBB
+=========
+
+
+
+Intel Threading Building Blocks
+-------------------------------
+
+Intel Threading Building Blocks (Intel TBB) is a library that supports
+scalable parallel programming using standard ISO C++ code. It does not
+require special languages or compilers. To use the library, you specify
+tasks, not threads, and let the library map tasks onto threads in an
+efficient manner. The tasks are executed by a runtime scheduler and may
+be offloaded to [MIC
+accelerator](../intel-xeon-phi.html).
+
+Intel TBB version 4.1 is available on Anselm
+
+ $ module load tbb
+
+The module sets up environment variables, required for linking and
+running tbb enabled applications.
+
+Link the tbb library, using -ltbb
+
+Examples
+--------
+
+Number of examples, demonstrating use of TBB and its built-in schedulerÂ
+is available on Anselm, in the $TBB_EXAMPLES directory.
+
+ $ module load intel
+ $ module load tbb
+ $ cp -a $TBB_EXAMPLES/common $TBB_EXAMPLES/parallel_reduce /tmp/
+ $ cd /tmp/parallel_reduce/primes
+ $ icc -O2 -DNDEBUG -o primes.x main.cpp primes.cpp -ltbb
+ $ ./primes.x
+
+In this example, we compile, link and run the primes example,
+demonstrating use of parallel task-based reduce in computation of prime
+numbers.
+
+You will need the tbb module loaded to run the tbb enabled executable.
+This may be avoided, by compiling library search paths into the
+executable.
+
+ $ icc -O2 -o primes.x main.cpp primes.cpp -Wl,-rpath=$LIBRARY_PATH -ltbb
+
+Further reading
+---------------
+
+Read more on Intel website,
+<http://software.intel.com/sites/products/documentation/doclib/tbb_sa/help/index.htm>
+
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+Intel Xeon Phi
+==============
+
+A guide to Intel Xeon Phi usage
+
+
+
+Intel Xeon Phi can be programmed in several modes. The default mode on
+Anselm is offload mode, but all modes described in this document are
+supported.
+
+Intel Utilities for Xeon Phi
+----------------------------
+
+To get access to a compute node with Intel Xeon Phi accelerator, use the
+PBS interactive session
+
+ $ qsub -I -q qmic -A NONE-0-0
+
+To set up the environment module "Intel" has to be loaded
+
+ $ module load intel/13.5.192
+
+Information about the hardware can be obtained by running
+the micinfo program on the host.
+
+ $ /usr/bin/micinfo
+
+The output of the "micinfo" utility executed on one of the Anselm node
+is as follows. (note: to get PCIe related details the command has to be
+run with root privileges)
+
+ MicInfo Utility Log
+
+ Created Mon Jul 22 00:23:50 2013
+
+ Â Â Â Â Â Â Â System Info
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â HOST OSÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â : Linux
+                OS Version             : 2.6.32-279.5.2.bl6.Bull.33.x86_64
+                Driver Version         : 6720-15
+                MPSS Version           : 2.1.6720-15
+                Host Physical Memory   : 98843 MB
+
+ Device No: 0, Device Name: mic0
+
+ Â Â Â Â Â Â Â Version
+                Flash Version           : 2.1.03.0386
+                SMC Firmware Version    : 1.15.4830
+                SMC Boot Loader Version : 1.8.4326
+                uOS Version             : 2.6.38.8-g2593b11
+                Device Serial Number    : ADKC30102482
+
+ Â Â Â Â Â Â Â Board
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Vendor IDÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â : 0x8086
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Device IDÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â : 0x2250
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Subsystem IDÂ Â Â Â Â Â Â Â Â Â Â Â : 0x2500
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Coprocessor Stepping IDÂ : 3
+                PCIe Width              : x16
+                PCIe Speed              : 5 GT/s
+                PCIe Max payload size   : 256 bytes
+                PCIe Max read req size  : 512 bytes
+                Coprocessor Model       : 0x01
+                Coprocessor Model Ext   : 0x00
+                Coprocessor Type        : 0x00
+                Coprocessor Family      : 0x0b
+                Coprocessor Family Ext  : 0x00
+                Coprocessor Stepping    : B1
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Board SKUÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â : B1PRQ-5110P/5120D
+                ECC Mode                : Enabled
+                SMC HW Revision         : Product 225W Passive CS
+
+ Â Â Â Â Â Â Â Cores
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Total No of Active Cores : 60
+                Voltage                 : 1032000 uV
+                Frequency               : 1052631 kHz
+
+ Â Â Â Â Â Â Â Thermal
+                Fan Speed Control       : N/A
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Fan RPMÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â : N/A
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Fan PWMÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â : N/A
+                Die Temp                : 49 C
+
+ Â Â Â Â Â Â Â GDDR
+                GDDR Vendor             : Elpida
+                GDDR Version            : 0x1
+                GDDR Density            : 2048 Mb
+                GDDR Size               : 7936 MB
+                GDDR Technology         : GDDR5
+                GDDR Speed              : 5.000000 GT/s
+                GDDR Frequency          : 2500000 kHz
+                GDDR Voltage            : 1501000 uV
+
+Offload Mode
+------------
+
+To compile a code for Intel Xeon Phi a MPSS stack has to be installed on
+the machine where compilation is executed. Currently the MPSS stack is
+only installed on compute nodes equipped with accelerators.
+
+ $ qsub -I -q qmic -A NONE-0-0
+ $ module load intel/13.5.192
+
+For debugging purposes it is also recommended to set environment
+variable "OFFLOAD_REPORT". Value can be set from 0 to 3, where higher
+number means more debugging information.
+
+ export OFFLOAD_REPORT=3
+
+A very basic example of code that employs offload programming technique
+is shown in the next listing. Please note that this code is sequential
+and utilizes only single core of the accelerator.
+
+ $ vim source-offload.cpp
+
+ #include <iostream>
+
+ int main(int argc, char* argv[])
+ {
+ Â Â Â const int niter = 100000;
+ Â Â Â double result = 0;
+
+ Â #pragma offload target(mic)
+ Â Â Â for (int i = 0; i < niter; ++i) {
+ Â Â Â Â Â Â Â const double t = (i + 0.5) / niter;
+ Â Â Â Â Â Â Â result += 4.0 / (t * t + 1.0);
+ Â Â Â }
+ Â Â Â result /= niter;
+ Â Â Â std::cout << "Pi ~ " << result << 'n';
+ }
+
+To compile a code using Intel compiler run
+
+ $ icc source-offload.cpp -o bin-offload
+
+To execute the code, run the following command on the host
+
+ ./bin-offload
+
+### Parallelization in Offload Mode Using OpenMP
+
+One way of paralelization a code for Xeon Phi is using OpenMP
+directives. The following example shows code for parallel vector
+addition.Â
+
+ $ vim ./vect-add
+
+ #include <stdio.h>
+
+ typedef int T;
+
+ #define SIZE 1000
+
+ #pragma offload_attribute(push, target(mic))
+ T in1[SIZE];
+ T in2[SIZE];
+ T res[SIZE];
+ #pragma offload_attribute(pop)
+
+ // MIC function to add two vectors
+ __attribute__((target(mic))) add_mic(T *a, T *b, T *c, int size) {
+ Â int i = 0;
+ Â #pragma omp parallel for
+ Â Â Â for (i = 0; i < size; i++)
+ Â Â Â Â Â c[i] = a[i] + b[i];
+ }
+
+ // CPU function to add two vectors
+ void add_cpu (T *a, T *b, T *c, int size) {
+ Â int i;
+ Â for (i = 0; i < size; i++)
+ Â Â Â c[i] = a[i] + b[i];
+ }
+
+ // CPU function to generate a vector of random numbers
+ void random_T (T *a, int size) {
+ Â int i;
+ Â for (i = 0; i < size; i++)
+ Â Â Â a[i] = rand() % 10000; // random number between 0 and 9999
+ }
+
+ // CPU function to compare two vectors
+ int compare(T *a, T *b, T size ){
+ Â int pass = 0;
+ Â int i;
+ Â for (i = 0; i < size; i++){
+ Â Â Â if (a[i] != b[i]) {
+ Â Â Â Â Â printf("Value mismatch at location %d, values %d and %dn",i, a[i], b[i]);
+ Â Â Â Â Â pass = 1;
+ Â Â Â }
+ Â }
+ Â if (pass == 0) printf ("Test passedn"); else printf ("Test Failedn");
+ Â return pass;
+ }
+
+ int main()
+ {
+ Â int i;
+ Â random_T(in1, SIZE);
+ Â random_T(in2, SIZE);
+
+ Â #pragma offload target(mic) in(in1,in2)Â inout(res)
+ Â {
+
+ Â Â Â // Parallel loop from main function
+ Â Â Â #pragma omp parallel for
+ Â Â Â for (i=0; i<SIZE; i++)
+ Â Â Â Â Â res[i] = in1[i] + in2[i];
+
+ Â Â Â // or parallel loop is called inside the function
+ Â Â Â add_mic(in1, in2, res, SIZE);
+
+ Â }
+
+ Â //Check the results with CPU implementation
+ Â T res_cpu[SIZE];
+ Â add_cpu(in1, in2, res_cpu, SIZE);
+ Â compare(res, res_cpu, SIZE);
+
+ }
+
+During the compilation Intel compiler shows which loops have been
+vectorized in both host and accelerator. This can be enabled with
+compiler option "-vec-report2". To compile and execute the code run
+
+ $ icc vect-add.c -openmp_report2 -vec-report2 -o vect-add
+
+ $ ./vect-add
+
+Some interesting compiler flags useful not only for code debugging are:
+
+Debugging
+Â openmp_report[0|1|2] - controls the compiler based vectorization
+diagnostic level
+Â vec-report[0|1|2] - controls the OpenMP parallelizer diagnostic
+level
+
+Performance ooptimization
+Â xhost - FOR HOST ONLY - to generate AVX (Advanced Vector Extensions)
+instructions.
+
+Automatic Offload using Intel MKL Library
+-----------------------------------------
+
+Intel MKL includes an Automatic Offload (AO) feature that enables
+computationally intensive MKL functions called in user code to benefit
+from attached Intel Xeon Phi coprocessors automatically and
+transparently.
+
+Behavioral of automatic offload mode is controlled by functions called
+within the program or by environmental variables. Complete list of
+controls is listed [
+here](http://software.intel.com/sites/products/documentation/doclib/mkl_sa/11/mkl_userguide_lnx/GUID-3DC4FC7D-A1E4-423D-9C0C-06AB265FFA86.htm).
+
+The Automatic Offload may be enabled by either an MKL function call
+within the code:
+
+ mkl_mic_enable();
+
+or by setting environment variable
+
+ $ export MKL_MIC_ENABLE=1
+
+To get more information about automatic offload please refer to "[Using
+Intel® MKL Automatic Offload on Intel ® Xeon Phi™
+Coprocessors](http://software.intel.com/sites/default/files/11MIC42_How_to_Use_MKL_Automatic_Offload_0.pdf)"
+white paper or [ Intel MKL
+documentation](https://software.intel.com/en-us/articles/intel-math-kernel-library-documentation).
+
+### Automatic offload example
+
+At first get an interactive PBS session on a node with MIC accelerator
+and load "intel" module that automatically loads "mkl" module as well.
+
+ $ qsub -I -q qmic -A OPEN-0-0 -l select=1:ncpus=16
+ $ module load intel
+
+Following example show how to automatically offload an SGEMM (single
+precision - g dir="auto">eneral matrix multiply) function to
+MIC coprocessor. The code can be copied to a file and compiled without
+any necessary modification.Â
+
+ $ vim sgemm-ao-short.c
+
+ #include <stdio.h>
+ #include <stdlib.h>
+ #include <malloc.h>
+ #include <stdint.h>
+
+ #include "mkl.h"
+
+ int main(int argc, char **argv)
+ {
+ Â Â Â Â Â Â Â float *A, *B, *C; /* Matrices */
+
+ Â Â Â Â Â Â Â MKL_INT N = 2560; /* Matrix dimensions */
+ Â Â Â Â Â Â Â MKL_INT LD = N; /* Leading dimension */
+ Â Â Â Â Â Â Â int matrix_bytes; /* Matrix size in bytes */
+ Â Â Â Â Â Â Â int matrix_elements; /* Matrix size in elements */
+
+ Â Â Â Â Â Â Â float alpha = 1.0, beta = 1.0; /* Scaling factors */
+ Â Â Â Â Â Â Â char transa = 'N', transb = 'N'; /* Transposition options */
+
+ Â Â Â Â Â Â Â int i, j; /* Counters */
+
+ Â Â Â Â Â Â Â matrix_elements = N * N;
+ Â Â Â Â Â Â Â matrix_bytes = sizeof(float) * matrix_elements;
+
+ Â Â Â Â Â Â Â /* Allocate the matrices */
+ Â Â Â Â Â Â Â A = malloc(matrix_bytes); B = malloc(matrix_bytes); C = malloc(matrix_bytes);
+
+ Â Â Â Â Â Â Â /* Initialize the matrices */
+ Â Â Â Â Â Â Â for (i = 0; i < matrix_elements; i++) {
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â A[i] = 1.0; B[i] = 2.0; C[i] = 0.0;
+ Â Â Â Â Â Â Â }
+
+ Â Â Â Â Â Â Â printf("Computing SGEMM on the hostn");
+ Â Â Â Â Â Â Â sgemm(&transa, &transb, &N, &N, &N, &alpha, A, &N, B, &N, &beta, C, &N);
+
+ Â Â Â Â Â Â Â printf("Enabling Automatic Offloadn");
+ Â Â Â Â Â Â Â /* Alternatively, set environment variable MKL_MIC_ENABLE=1 */
+ Â Â Â Â Â Â Â mkl_mic_enable();
+ Â Â Â Â Â Â Â
+ Â Â Â Â Â Â Â int ndevices = mkl_mic_get_device_count(); /* Number of MIC devices */
+        printf("Automatic Offload enabled: %d MIC devices presentn",  ndevices);
+
+ Â Â Â Â Â Â Â printf("Computing SGEMM with automatic workdivisionn");
+ Â Â Â Â Â Â Â sgemm(&transa, &transb, &N, &N, &N, &alpha, A, &N, B, &N, &beta, C, &N);
+
+ Â Â Â Â Â Â Â /* Free the matrix memory */
+ Â Â Â Â Â Â Â free(A); free(B); free(C);
+
+ Â Â Â Â Â Â Â printf("Donen");
+
+ Â Â Â return 0;
+ }
+
+Please note: This example is simplified version of an example from MKL.
+The expanded version can be found here:
+$MKL_EXAMPLES/mic_ao/blasc/source/sgemm.c**
+
+To compile a code using Intel compiler use:
+
+ $ icc -mkl sgemm-ao-short.c -o sgemm
+
+For debugging purposes enable the offload report to see more information
+about automatic offloading.
+
+ $ export OFFLOAD_REPORT=2
+
+The output of a code should look similar to following listing, where
+lines starting with [MKL] are generated by offload reporting:
+
+ Computing SGEMM on the host
+ Enabling Automatic Offload
+ Automatic Offload enabled: 1 MIC devices present
+ Computing SGEMM with automatic workdivision
+ [MKL] [MIC --] [AO Function]Â Â Â SGEMM
+ [MKL] [MIC --] [AO SGEMM Workdivision]Â 0.00 1.00
+ [MKL] [MIC 00] [AO SGEMM CPU Time]Â Â Â Â Â 0.463351 seconds
+ [MKL] [MIC 00] [AO SGEMM MIC Time]Â Â Â Â Â 0.179608 seconds
+ [MKL] [MIC 00] [AO SGEMM CPU->MIC Data] 52428800 bytes
+ [MKL] [MIC 00] [AO SGEMM MIC->CPU Data] 26214400 bytes
+ Done
+
+Â
+
+Native Mode
+-----------
+
+In the native mode a program is executed directly on Intel Xeon Phi
+without involvement of the host machine. Similarly to offload mode, the
+code is compiled on the host computer with Intel compilers.
+
+To compile a code user has to be connected to a compute with MIC and
+load Intel compilers module. To get an interactive session on a compute
+node with an Intel Xeon Phi and load the module use following commands:Â
+
+ $ qsub -I -q qmic -A NONE-0-0
+
+ $ module load intel/13.5.192
+
+Please note that particular version of the Intel module is specified.
+This information is used later to specify the correct library paths.
+
+To produce a binary compatible with Intel Xeon Phi architecture user has
+to specify "-mmic" compiler flag. Two compilation examples are shown
+below. The first example shows how to compile OpenMP parallel code
+"vect-add.c" for host only:
+
+ $ icc -xhost -no-offload -fopenmp vect-add.c -o vect-add-host
+
+To run this code on host, use:
+
+ $ ./vect-add-host
+
+The second example shows how to compile the same code for Intel Xeon
+Phi:
+
+ $ icc -mmic -fopenmp vect-add.c -o vect-add-mic
+
+### Execution of the Program in Native Mode on Intel Xeon Phi
+
+The user access to the Intel Xeon Phi is through the SSH. Since user
+home directories are mounted using NFS on the accelerator, users do not
+have to copy binary files or libraries between the host and accelerator.
+Â
+
+To connect to the accelerator run:
+
+ $ ssh mic0
+
+If the code is sequential, it can be executed directly:
+
+ mic0 $ ~/path_to_binary/vect-add-seq-mic
+
+If the code is parallelized using OpenMP a set of additional libraries
+is required for execution. To locate these libraries new path has to be
+added to the LD_LIBRARY_PATH environment variable prior to the
+execution:
+
+ mic0 $ export LD_LIBRARY_PATH=/apps/intel/composer_xe_2013.5.192/compiler/lib/mic:$LD_LIBRARY_PATH
+
+Please note that the path exported in the previous example contains path
+to a specific compiler (here the version is 5.192). This version number
+has to match with the version number of the Intel compiler module that
+was used to compile the code on the host computer.
+
+For your information the list of libraries and their location required
+for execution of an OpenMP parallel code on Intel Xeon Phi is:
+
+/apps/intel/composer_xe_2013.5.192/compiler/lib/mic
+
+libiomp5.so
+libimf.so
+libsvml.so
+libirng.so
+libintlc.so.5
+
+Finally, to run the compiled code use:
+
+ $ ~/path_to_binary/vect-add-mic
+
+OpenCL
+-------------------
+
+OpenCL (Open Computing Language) is an open standard for
+general-purpose parallel programming for diverse mix of multi-core CPUs,
+GPU coprocessors, and other parallel processors. OpenCL provides a
+flexible execution model and uniform programming environment for
+software developers to write portable code for systems running on both
+the CPU and graphics processors or accelerators like the Intel® Xeon
+Phi.
+
+On Anselm OpenCL is installed only on compute nodes with MIC
+accelerator, therefore OpenCL code can be compiled only on these nodes.
+
+ module load opencl-sdk opencl-rt
+
+Always load "opencl-sdk" (providing devel files like headers) and
+"opencl-rt" (providing dynamic library libOpenCL.so) modules to compile
+and link OpenCL code. Load "opencl-rt" for running your compiled code.
+
+There are two basic examples of OpenCL code in the following
+directory:
+
+ /apps/intel/opencl-examples/
+
+First example "CapsBasic" detects OpenCL compatible hardware, here
+CPU and MIC, and prints basic information about the capabilities of
+it.Â
+
+ /apps/intel/opencl-examples/CapsBasic/capsbasic
+
+To compile and run the example copy it to your home directory, get
+a PBS interactive session on of the nodes with MIC and run make for
+compilation. Make files are very basic and shows how the OpenCL code can
+be compiled on Anselm.
+
+ $ cp /apps/intel/opencl-examples/CapsBasic/* .
+ $ qsub -I -q qmic -A NONE-0-0
+ $ make
+
+The compilation command for this example is:
+
+ $ g++ capsbasic.cpp -lOpenCL -o capsbasic -I/apps/intel/opencl/include/
+
+After executing the complied binary file, following output should
+be displayed.
+
+ ./capsbasic
+
+ Number of available platforms: 1
+ Platform names:
+ Â Â Â [0] Intel(R) OpenCL [Selected]
+ Number of devices available for each type:
+ Â Â Â CL_DEVICE_TYPE_CPU: 1
+ Â Â Â CL_DEVICE_TYPE_GPU: 0
+ Â Â Â CL_DEVICE_TYPE_ACCELERATOR: 1
+
+ ** Detailed information for each device ***
+
+ CL_DEVICE_TYPE_CPU[0]
+ Â Â Â CL_DEVICE_NAME:Â Â Â Â Â Â Â Intel(R) Xeon(R) CPU E5-2470 0 @ 2.30GHz
+ Â Â Â CL_DEVICE_AVAILABLE: 1
+
+ ...
+
+ CL_DEVICE_TYPE_ACCELERATOR[0]
+ Â Â Â CL_DEVICE_NAME: Intel(R) Many Integrated Core Acceleration Card
+ Â Â Â CL_DEVICE_AVAILABLE: 1
+
+ ...
+
+More information about this example can be found on Intel website:
+<http://software.intel.com/en-us/vcsource/samples/caps-basic/>
+
+The second example that can be found in
+"/apps/intel/opencl-examples" >directory is General Matrix
+Multiply. You can follow the the same procedure to download the example
+to your directory and compile it.Â
+
+ $ cp -r /apps/intel/opencl-examples/* .
+ $ qsub -I -q qmic -A NONE-0-0
+ $ cd GEMM
+ $ make
+
+The compilation command for this example is:
+
+ $ g++ cmdoptions.cpp gemm.cpp ../common/basic.cpp ../common/cmdparser.cpp ../common/oclobject.cpp -I../common -lOpenCL -o gemm -I/apps/intel/opencl/include/
+
+To see the performance of Intel Xeon Phi performing the DGEMM run
+the example as follows:
+
+ ./gemm -d 1
+ Platforms (1):
+ [0] Intel(R) OpenCL [Selected]
+ Devices (2):
+ [0] Intel(R) Xeon(R) CPU E5-2470 0 @ 2.30GHz
+ [1] Intel(R) Many Integrated Core Acceleration Card [Selected]
+ Build program options: "-DT=float -DTILE_SIZE_M=1 -DTILE_GROUP_M=16 -DTILE_SIZE_N=128 -DTILE_GROUP_N=1 -DTILE_SIZE_K=8"
+ Running gemm_nn kernel with matrix size: 3968x3968
+ Memory row stride to ensure necessary alignment: 15872 bytes
+ Size of memory region for one matrix: 62980096 bytes
+ Using alpha = 0.57599 and beta = 0.872412
+ ...
+ Host time: 0.292953 sec.
+ Host perf: 426.635 GFLOPS
+ Host time: 0.293334 sec.
+ Host perf: 426.081 GFLOPS
+ ...
+
+Please note: GNU compiler is used to compile the OpenCL codes for
+Intel MIC. You do not need to load Intel compiler module.
+
+MPIÂ
+-----------------
+
+### Environment setup and compilation
+
+Again an MPI code for Intel Xeon Phi has to be compiled on a compute
+node with accelerator and MPSS software stack installed. To get to a
+compute node with accelerator use:
+
+ $ qsub -I -q qmic -A NONE-0-0
+
+The only supported implementation of MPI standard for Intel Xeon Phi is
+Intel MPI. To setup a fully functional development environment a
+combination of Intel compiler and Intel MPI has to be used. On a host
+load following modules before compilation:
+
+ $ module load intel/13.5.192 impi/4.1.1.036
+
+To compile an MPI code for host use:
+
+ $ mpiicc -xhost -o mpi-test mpi-test.c
+
+To compile the same code for Intel Xeon Phi architecture use:
+
+ $ mpiicc -mmic -o mpi-test-mic mpi-test.c
+
+An example of basic MPI version of "hello-world" example in C language,
+that can be executed on both host and Xeon Phi is (can be directly copy
+and pasted to a .c file)
+
+ #include <stdio.h>
+ #include <mpi.h>
+
+ int main (argc, argv)
+ Â Â Â Â int argc;
+ Â Â Â Â char *argv[];
+ {
+ Â int rank, size;
+
+ Â int len;
+ Â char node[MPI_MAX_PROCESSOR_NAME];
+
+ Â MPI_Init (&argc, &argv);Â Â Â Â Â /* starts MPI */
+ Â MPI_Comm_rank (MPI_COMM_WORLD, &rank);Â Â Â Â Â Â Â /* get current process id */
+ Â MPI_Comm_size (MPI_COMM_WORLD, &size);Â Â Â Â Â Â Â /* get number of processes */
+
+ Â MPI_Get_processor_name(node,&len);
+
+ Â printf( "Hello world from process %d of %d on host %s n", rank, size, node );
+ Â MPI_Finalize();
+ Â return 0;
+ }
+
+### MPI programming models
+
+Intel MPI for the Xeon Phi coprocessors offers different MPI
+programming models:
+
+Host-only model** - all MPI ranks reside on the host. The coprocessors
+can be used by using offload pragmas. (Using MPI calls inside offloaded
+code is not supported.)**
+
+Coprocessor-only model** - all MPI ranks reside only on the
+coprocessors.
+
+Symmetric model** - the MPI ranks reside on both the host and the
+coprocessor. Most general MPI case.
+
+###Host-only model
+
+In this case all environment variables are set by modules,
+so to execute the compiled MPI program on a single node, use:
+
+ $ mpirun -np 4 ./mpi-test
+
+The output should be similar to:
+
+ Hello world from process 1 of 4 on host cn207
+ Hello world from process 3 of 4 on host cn207
+ Hello world from process 2 of 4 on host cn207
+ Hello world from process 0 of 4 on host cn207
+
+### Coprocessor-only model
+
+There are two ways how to execute an MPI code on a single
+coprocessor: 1.) lunch the program using "**mpirun**" from the
+coprocessor; or 2.) lunch the task using "**mpiexec.hydra**" from a
+host.
+
+Execution on coprocessor**Â
+
+Similarly to execution of OpenMP programs in native mode, since the
+environmental module are not supported on MIC, user has to setup paths
+to Intel MPI libraries and binaries manually. One time setup can be done
+by creating a "**.profile**" file in user's home directory. This file
+sets up the environment on the MIC automatically once user access to the
+accelerator through the SSH.
+
+ $ vim ~/.profile
+
+ PS1='[u@h W]$ '
+ export PATH=/usr/bin:/usr/sbin:/bin:/sbin
+
+ #OpenMP
+ export LD_LIBRARY_PATH=/apps/intel/composer_xe_2013.5.192/compiler/lib/mic:$LD_LIBRARY_PATH
+
+ #Intel MPI
+ export LD_LIBRARY_PATH=/apps/intel/impi/4.1.1.036/mic/lib/:$LD_LIBRARY_PATH
+ export PATH=/apps/intel/impi/4.1.1.036/mic/bin/:$PATH
+
+Please note:
+Â - this file sets up both environmental variable for both MPI and OpenMP
+libraries.
+Â - this file sets up the paths to a particular version of Intel MPI
+library and particular version of an Intel compiler. These versions have
+to match with loaded modules.
+
+To access a MIC accelerator located on a node that user is currently
+connected to, use:
+
+ $ ssh mic0
+
+or in case you need specify a MIC accelerator on a particular node, use:
+
+ $ ssh cn207-mic0
+
+To run the MPI code in parallel on multiple core of the accelerator,
+use:
+
+ $ mpirun -np 4 ./mpi-test-mic
+
+The output should be similar to:
+
+ Hello world from process 1 of 4 on host cn207-mic0
+ Hello world from process 2 of 4 on host cn207-mic0
+ Hello world from process 3 of 4 on host cn207-mic0
+ Hello world from process 0 of 4 on host cn207-mic0
+
+**Execution on host**
+
+If the MPI program is launched from host instead of the coprocessor, the
+environmental variables are not set using the ".profile" file. Therefore
+user has to specify library paths from the command line when calling
+"mpiexec".
+
+First step is to tell mpiexec that the MPI should be executed on a local
+accelerator by setting up the environmental variable "I_MPI_MIC"
+
+ $ export I_MPI_MIC=1
+
+Now the MPI program can be executed as:
+
+ $ mpiexec.hydra -genv LD_LIBRARY_PATH /apps/intel/impi/4.1.1.036/mic/lib/ -host mic0 -n 4 ~/mpi-test-mic
+
+or using mpirun
+
+ $ mpirun -genv LD_LIBRARY_PATH /apps/intel/impi/4.1.1.036/mic/lib/ -host mic0 -n 4 ~/mpi-test-mic
+
+Please note:
+Â - the full path to the binary has to specified (here:
+"**>~/mpi-test-mic**")
+Â - the LD_LIBRARY_PATH has to match with Intel MPI module used to
+compile the MPI code
+
+The output should be again similar to:
+
+ Hello world from process 1 of 4 on host cn207-mic0
+ Hello world from process 2 of 4 on host cn207-mic0
+ Hello world from process 3 of 4 on host cn207-mic0
+ Hello world from process 0 of 4 on host cn207-mic0
+
+Please note that the "mpiexec.hydra" requires a file
+"**>pmi_proxy**" from Intel MPI library to be copied to the
+MIC filesystem. If the file is missing please contact the system
+administrators. A simple test to see if the file is present is to
+execute:
+
+ Â Â $ ssh mic0 ls /bin/pmi_proxy
+ Â /bin/pmi_proxy
+
+**Execution on host - MPI processes distributed over multiple
+accelerators on multiple nodes**
+
+To get access to multiple nodes with MIC accelerator, user has to
+use PBS to allocate the resources. To start interactive session, that
+allocates 2 compute nodes = 2 MIC accelerators run qsub command with
+following parameters:
+
+ $ qsub -I -q qmic -A NONE-0-0 -l select=2:ncpus=16
+
+ $ module load intel/13.5.192 impi/4.1.1.036
+
+This command connects user through ssh to one of the nodes
+immediately. To see the other nodes that have been allocated use:
+
+ $ cat $PBS_NODEFILE
+
+For example:
+
+ cn204.bullx
+ cn205.bullx
+
+This output means that the PBS allocated nodes cn204 and cn205,
+which means that user has direct access to "**cn204-mic0**" and
+"**cn-205-mic0**" accelerators.
+
+Please note: At this point user can connect to any of the
+allocated nodes or any of the allocated MIC accelerators using ssh:
+- to connect to the second node : ** $ ssh
+cn205**
+- to connect to the accelerator on the first node from the first
+node: **$ ssh cn204-mic0** or
+ $ ssh mic0**
+-** to connect to the accelerator on the second node from the first
+node: **$ ssh cn205-mic0**
+
+At this point we expect that correct modules are loaded and binary
+is compiled. For parallel execution the mpiexec.hydra is used.
+Again the first step is to tell mpiexec that the MPI can be executed on
+MIC accelerators by setting up the environmental variable "I_MPI_MIC"
+
+ $ export I_MPI_MIC=1
+
+The launch the MPI program use:
+
+ $ mpiexec.hydra -genv LD_LIBRARY_PATH /apps/intel/impi/4.1.1.036/mic/lib/
+ -genv I_MPI_FABRICS_LIST tcp
+ Â -genv I_MPI_FABRICS shm:tcp
+ Â -genv I_MPI_TCP_NETMASK=10.1.0.0/16
+ -host cn204-mic0 -n 4 ~/mpi-test-mic
+ : -host cn205-mic0 -n 6 ~/mpi-test-mic
+
+or using mpirun:
+
+ $ mpirun -genv LD_LIBRARY_PATH /apps/intel/impi/4.1.1.036/mic/lib/
+ -genv I_MPI_FABRICS_LIST tcp
+ Â -genv I_MPI_FABRICS shm:tcp
+ Â -genv I_MPI_TCP_NETMASK=10.1.0.0/16
+ -host cn204-mic0 -n 4 ~/mpi-test-mic
+ : -host cn205-mic0 -n 6 ~/mpi-test-mic
+
+In this case four MPI processes are executed on accelerator cn204-mic
+and six processes are executed on accelerator cn205-mic0. The sample
+output (sorted after execution) is:
+
+ Hello world from process 0 of 10 on host cn204-mic0
+ Hello world from process 1 of 10 on host cn204-mic0
+ Hello world from process 2 of 10 on host cn204-mic0
+ Hello world from process 3 of 10 on host cn204-mic0
+ Hello world from process 4 of 10 on host cn205-mic0
+ Hello world from process 5 of 10 on host cn205-mic0
+ Hello world from process 6 of 10 on host cn205-mic0
+ Hello world from process 7 of 10 on host cn205-mic0
+ Hello world from process 8 of 10 on host cn205-mic0
+ Hello world from process 9 of 10 on host cn205-mic0
+
+The same way MPI program can be executed on multiple hosts:Â
+
+ $ mpiexec.hydra -genv LD_LIBRARY_PATH /apps/intel/impi/4.1.1.036/mic/lib/
+ -genv I_MPI_FABRICS_LIST tcp
+ Â -genv I_MPI_FABRICS shm:tcp
+ Â -genv I_MPI_TCP_NETMASK=10.1.0.0/16
+ -host cn204 -n 4 ~/mpi-test
+ : -host cn205 -n 6 ~/mpi-test
+
+###Symmetric model
+
+In a symmetric mode MPI programs are executed on both host
+computer(s) and MIC accelerator(s). Since MIC has a different
+architecture and requires different binary file produced by the Intel
+compiler two different files has to be compiled before MPI program is
+executed.
+
+In the previous section we have compiled two binary files, one for
+hosts "**mpi-test**" and one for MIC accelerators "**mpi-test-mic**".
+These two binaries can be executed at once using mpiexec.hydra:
+
+ $ mpiexec.hydra
+ -genv I_MPI_FABRICS_LIST tcp
+ -genv I_MPI_FABRICS shm:tcp
+ Â -genv I_MPI_TCP_NETMASK=10.1.0.0/16
+ -genv LD_LIBRARY_PATH /apps/intel/impi/4.1.1.036/mic/lib/
+ -host cn205 -n 2 ~/mpi-test
+ : -host cn205-mic0 -n 2 ~/mpi-test-mic
+
+In this example the first two parameters (line 2 and 3) sets up required
+environment variables for execution. The third line specifies binary
+that is executed on host (here cn205) and the last line specifies the
+binary that is execute on the accelerator (here cn205-mic0).
+
+The output of the program is:
+
+ Hello world from process 0 of 4 on host cn205
+ Hello world from process 1 of 4 on host cn205
+ Hello world from process 2 of 4 on host cn205-mic0
+ Hello world from process 3 of 4 on host cn205-mic0
+
+The execution procedure can be simplified by using the mpirun
+command with the machine file a a parameter. Machine file contains list
+of all nodes and accelerators that should used to execute MPI processes.
+
+An example of a machine file that uses 2 >hosts (**cn205**
+and **cn206**) and 2 accelerators **(cn205-mic0** and **cn206-mic0**) to
+run 2 MPI processes on each of them:
+
+ $ cat hosts_file_mix
+ cn205:2
+ cn205-mic0:2
+ cn206:2
+ cn206-mic0:2
+
+In addition if a naming convention is set in a way that the name
+of the binary for host is **"bin_name"**Â and the name of the binary
+for the accelerator is **"bin_name-mic"** then by setting up the
+environment variable **I_MPI_MIC_POSTFIX** to **"-mic"** user do not
+have to specify the names of booth binaries. In this case mpirun needs
+just the name of the host binary file (i.e. "mpi-test") and uses the
+suffix to get a name of the binary for accelerator (i..e.
+"mpi-test-mic").
+
+ $ export I_MPI_MIC_POSTFIX=-mic
+
+Â >To run the MPI code using mpirun and the machine file
+"hosts_file_mix" use:
+
+ $ mpirun
+ -genv I_MPI_FABRICS shm:tcp
+ -genv LD_LIBRARY_PATH /apps/intel/impi/4.1.1.036/mic/lib/
+ -genv I_MPI_FABRICS_LIST tcp
+ Â -genv I_MPI_FABRICS shm:tcp
+ Â -genv I_MPI_TCP_NETMASK=10.1.0.0/16
+ -machinefile hosts_file_mix
+ ~/mpi-test
+
+A possible output of the MPI "hello-world" example executed on two
+hosts and two accelerators is:
+
+ Hello world from process 0 of 8 on host cn204
+ Hello world from process 1 of 8 on host cn204
+ Hello world from process 2 of 8 on host cn204-mic0
+ Hello world from process 3 of 8 on host cn204-mic0
+ Hello world from process 4 of 8 on host cn205
+ Hello world from process 5 of 8 on host cn205
+ Hello world from process 6 of 8 on host cn205-mic0
+ Hello world from process 7 of 8 on host cn205-mic0
+
+Please note: At this point the MPI communication between MIC
+accelerators on different nodes uses 1Gb Ethernet only.
+
+Using the PBS automatically generated node-files
+
+PBS also generates a set of node-files that can be used instead of
+manually creating a new one every time. Three node-files are genereated:
+
+**Host only node-file:**
+Â - /lscratch/${PBS_JOBID}/nodefile-cn
+MIC only node-file:
+Â - /lscratch/${PBS_JOBID}/nodefile-mic
+Host and MIC node-file:
+Â - /lscratch/${PBS_JOBID}/nodefile-mix
+
+Please note each host or accelerator is listed only per files. User has
+to specify how many jobs should be executed per node using "-n"
+parameter of the mpirun command.
+
+Optimization
+------------
+
+For more details about optimization techniques please read Intel
+document [Optimization and Performance Tuning for Intel® Xeon Phi™
+Coprocessors](http://software.intel.com/en-us/articles/optimization-and-performance-tuning-for-intel-xeon-phi-coprocessors-part-1-optimization "http://software.intel.com/en-us/articles/optimization-and-performance-tuning-for-intel-xeon-phi-coprocessors-part-1-optimization")
+
+Â
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/isv_licenses.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/isv_licenses.md
new file mode 100644
index 0000000000000000000000000000000000000000..719fa3fd918379f0dd6564387b74270fdc5be2bd
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/isv_licenses.md
@@ -0,0 +1,149 @@
+ISV Licenses
+============
+
+A guide to managing Independent Software Vendor licences
+
+
+
+On Anselm cluster there are also installed commercial software
+applications, also known as ISV (Independent Software Vendor), which are
+subjects to licensing. The licenses are limited and their usage may be
+restricted only to some users or user groups.
+
+Currently Flex License Manager based licensing is supported on the
+cluster for products Ansys, Comsol and Matlab. More information about
+the applications can be found in the general
+[Software](../software.1.html) section.
+
+If an ISV application was purchased for educational (research) purposes
+and also for commercial purposes, then there are always two separate
+versions maintained and suffix "edu" is used in the name of the
+non-commercial version.
+
+Overview of the licenses usage
+------------------------------
+
+The overview is generated every minute and is accessible from web or
+command line interface.
+
+### Web interface
+
+For each license there is a table, which provides the information about
+the name, number of available (purchased/licensed), number of used and
+number of free license features
+
+<https://extranet.it4i.cz/anselm/licenses>
+
+### Text interface
+
+For each license there is a unique text file, which provides the
+information about the name, number of available (purchased/licensed),
+number of used and number of free license features. The text files are
+accessible from the Anselm command prompt.
+
+ Product File with license state Note
+ ------ |---|---|------------------------------------------- ---------------------
+ ansys /apps/user/licenses/ansys_features_state.txt Commercial
+ comsol /apps/user/licenses/comsol_features_state.txt Commercial
+ comsol-edu /apps/user/licenses/comsol-edu_features_state.txt Non-commercial only
+ matlab /apps/user/licenses/matlab_features_state.txt Commercial
+ matlab-edu /apps/user/licenses/matlab-edu_features_state.txt Non-commercial only
+
+The file has a header which serves as a legend. All the info in the
+legend starts with a hash (#) so it can be easily filtered when parsing
+the file via a script.
+
+Example of the Commercial Matlab license state:
+
+ $ cat /apps/user/licenses/matlab_features_state.txt
+ # matlab
+ # -------------------------------------------------
+ # FEATURE TOTAL USED AVAIL
+ # -------------------------------------------------
+ MATLAB 1 1 0
+ SIMULINK 1 0 1
+ Curve_Fitting_Toolbox 1 0 1
+ Signal_Blocks 1 0 1
+ GADS_Toolbox 1 0 1
+ Image_Toolbox 1 0 1
+ Compiler 1 0 1
+ Neural_Network_Toolbox 1 0 1
+ Optimization_Toolbox 1 0 1
+ Signal_Toolbox 1 0 1
+ Statistics_Toolbox 1 0 1
+
+License tracking in PBS Pro scheduler and users usage
+-----------------------------------------------------
+
+Each feature of each license is accounted and checked by the scheduler
+of PBS Pro. If you ask for certain licences, the scheduler won't start
+the job until the asked licenses are free (available). This prevents to
+crash batch jobs, just because of
+ unavailability of the
+needed licenses.
+
+The general format of the name is:
+
+feature__APP__FEATURE**
+
+Names of applications (APP):
+
+- ansys
+- comsol
+- comsol-edu
+- matlab
+- matlab-edu
+
+Â
+
+To get the FEATUREs of a license take a look into the corresponding
+state file ([see above](isv_licenses.html#Licence)), or
+use:
+
+ |Application |List of provided features |
+ | --- | --- |
+ |ansys |<pre><code>$ grep -v "#" /apps/user/licenses/ansys_features_state.txt | cut -f1 -d' '</code></pre> |
+ |comsol |<pre><code>$ grep -v "#" /apps/user/licenses/comsol_features_state.txt | cut -f1 -d' '</code></pre> |
+ |comsol-edu |<pre><code>$ grep -v "#" /apps/user/licenses/comsol-edu_features_state.txt | cut -f1 -d' '</code></pre> |
+ |matlab |<pre><code>$ grep -v "#" /apps/user/licenses/matlab_features_state.txt | cut -f1 -d' '</code></pre> |
+ |matlab-edu |<pre><code>$ grep -v "#" /apps/user/licenses/matlab-edu_features_state.txt | cut -f1 -d' '</code></pre> |
+
+Â
+
+Example of PBS Pro resource name, based on APP and FEATURE name:
+
+<col width="33%" />
+<col width="33%" />
+<col width="33%" />
+ |Application |Feature |PBS Pro resource name |
+ | --- | --- |
+ |ansys |acfd |feature__ansys__acfd |
+ |ansys |aa_r |feature__ansys__aa_r |
+ |comsol |COMSOL |feature__comsol__COMSOL |
+ |comsol |HEATTRANSFER |feature__comsol__HEATTRANSFER |
+ |comsol-edu |COMSOLBATCH |feature__comsol-edu__COMSOLBATCH |
+ |comsol-edu |STRUCTURALMECHANICS |feature__comsol-edu__STRUCTURALMECHANICS |
+ |matlab |MATLAB |feature__matlab__MATLAB |
+ |matlab |Image_Toolbox |feature__matlab__Image_Toolbox |
+ |matlab-edu |MATLAB_Distrib_Comp_Engine |feature__matlab-edu__MATLAB_Distrib_Comp_Engine |
+ |matlab-edu |Image_Acquisition_Toolbox |feature__matlab-edu__Image_Acquisition_Toolbox\ |
+
+Be aware, that the resource names in PBS Pro are CASE SENSITIVE!**
+
+### Example of qsub statement
+
+Run an interactive PBS job with 1 Matlab EDU license, 1 Distributed
+Computing Toolbox and 32 Distributed Computing Engines (running on 32
+cores):
+
+ $ qsub -I -q qprod -A PROJECT_ID -l select=2:ncpus=16 -l feature__matlab-edu__MATLAB=1 -l feature__matlab-edu__Distrib_Computing_Toolbox=1 -l feature__matlab-edu__MATLAB_Distrib_Comp_Engine=32
+
+The license is used and accounted only with the real usage of the
+product. So in this example, the general Matlab is used after Matlab is
+run vy the user and not at the time, when the shell of the interactive
+job is started. Also the Distributed Computing licenses are used at the
+time, when the user uses the distributed parallel computation in Matlab
+(e. g. issues pmode start, matlabpool, etc.).
+
+Â
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/java.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/java.md
new file mode 100644
index 0000000000000000000000000000000000000000..9094578fb82ad669d7ec1cd25caaf132bc73fc22
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/java.md
@@ -0,0 +1,33 @@
+Java
+====
+
+Java on ANSELM
+
+
+
+Java is available on Anselm cluster. Activate java by loading the java
+module
+
+ $ module load java
+
+Note that the java module must be loaded on the compute nodes as well,
+in order to run java on compute nodes.
+
+Check for java version and path
+
+ $ java -version
+ $ which java
+
+With the module loaded, not only the runtime environment (JRE), but also
+the development environment (JDK) with the compiler is available.
+
+ $ javac -version
+ $ which javac
+
+Java applications may use MPI for interprocess communication, in
+conjunction with OpenMPI. Read more
+on <http://www.open-mpi.org/faq/?category=java>.
+This functionality is currently not supported on Anselm cluster. In case
+you require the java interface to MPI, please contact [Anselm
+support](https://support.it4i.cz/rt/).
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/kvirtualization.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/kvirtualization.md
new file mode 100644
index 0000000000000000000000000000000000000000..803b896d1f2dc44638431b0e9c4d24efd4699d7e
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/kvirtualization.md
@@ -0,0 +1,484 @@
+Virtualization
+==============
+
+Running virtual machines on compute nodes
+
+
+
+Introduction
+------------
+
+There are situations when Anselm's environment is not suitable for user
+needs.
+
+- Application requires different operating system (e.g Windows),
+ application is not available for Linux
+- Application requires different versions of base system libraries and
+ tools
+- Application requires specific setup (installation, configuration) of
+ complex software stack
+- Application requires privileged access to operating system
+- ... and combinations of above cases
+
+Â We offer solution for these cases - **virtualization**. Anselm's
+environment gives the possibility to run virtual machines on compute
+nodes. Users can create their own images of operating system with
+specific software stack and run instances of these images as virtual
+machines on compute nodes. Run of virtual machines is provided by
+standard mechanism of [Resource Allocation and Job
+Execution](../../resource-allocation-and-job-execution/introduction.html).
+
+Solution is based on QEMU-KVM software stack and provides
+hardware-assisted x86 virtualization.
+
+Limitations
+-----------
+
+Anselm's infrastructure was not designed for virtualization. Anselm's
+environment is not intended primary for virtualization, compute nodes,
+storages and all infrastructure of Anselm is intended and optimized for
+running HPC jobs, this implies suboptimal configuration of
+virtualization and limitations.
+
+Anselm's virtualization does not provide performance and all features of
+native environment. There is significant performance hit (degradation)
+in I/O performance (storage, network). Anselm's virtualization is not
+suitable for I/O (disk, network) intensive workloads.
+
+Virtualization has also some drawbacks, it is not so easy to setup
+efficient solution.
+
+Solution described in chapter
+[HOWTO](virtualization.html#howto)
+ is suitable for single node tasks, does not
+introduce virtual machine clustering.
+
+Please consider virtualization as last resort solution for your needs.
+
+Please consult use of virtualization with IT4Innovation's support.
+
+For running Windows application (when source code and Linux native
+application are not available) consider use of Wine, Windows
+compatibility layer. Many Windows applications can be run using Wine
+with less effort and better performance than when using virtualization.
+
+Licensing
+---------
+
+IT4Innovations does not provide any licenses for operating systems and
+software of virtual machines. Users are ( >
+in accordance with [Acceptable use policy
+document](http://www.it4i.cz/acceptable-use-policy.pdf))
+fully responsible for licensing all software running in virtual machines
+on Anselm. Be aware of complex conditions of licensing software in
+virtual environments.
+
+Users are responsible for licensing OS e.g. MS Windows and all software
+running in their virtual machines.
+
+Â HOWTO
+----------
+
+### Virtual Machine Job Workflow
+
+We propose this job workflow:
+
+Workflow](virtualization-job-workflow "Virtualization Job Workflow")
+
+Our recommended solution is that job script creates distinct shared job
+directory, which makes a central point for data exchange between
+Anselm's environment, compute node (host) (e.g HOME, SCRATCH, local
+scratch and other local or cluster filesystems) and virtual machine
+(guest). Job script links or copies input data and instructions what to
+do (run script) for virtual machine to job directory and virtual machine
+process input data according instructions in job directory and store
+output back to job directory. We recommend, that virtual machine is
+running in so called [snapshot
+mode](virtualization.html#snapshot-mode), image is
+immutable - image does not change, so one image can be used for many
+concurrent jobs.
+
+### Procedure
+
+1. Prepare image of your virtual machine
+2. Optimize image of your virtual machine for Anselm's virtualization
+3. Modify your image for running jobs
+4. Create job script for executing virtual machine
+5. Run jobs
+
+### Prepare image of your virtual machine
+
+You can either use your existing image or create new image from scratch.
+
+QEMU currently supports these image types or formats:
+
+- rawÂ
+- cloopÂ
+- cowÂ
+- qcowÂ
+- qcow2Â
+- vmdk - VMware 3 & 4, or 6 image format, for exchanging images with
+ that product
+- vdi - VirtualBox 1.1 compatible image format, for exchanging images
+ with VirtualBox.
+
+You can convert your existing image using qemu-img convert command.
+Supported formats of this command are: blkdebug blkverify bochs cloop
+cow dmg file ftp ftps host_cdrom host_device host_floppy http https
+nbd parallels qcow qcow2 qed raw sheepdog tftp vdi vhdx vmdk vpc vvfat.
+
+We recommend using advanced QEMU native image format qcow2.
+
+[More about QEMU
+Images](http://en.wikibooks.org/wiki/QEMU/Images)
+
+### Optimize image of your virtual machine
+
+Use virtio devices (for disk/drive and network adapter) and install
+virtio drivers (paravirtualized drivers) into virtual machine. There is
+significant performance gain when using virtio drivers. For more
+information see [Virtio
+Linux](http://www.linux-kvm.org/page/Virtio) and [Virtio
+Windows](http://www.linux-kvm.org/page/WindowsGuestDrivers/Download_Drivers).
+
+Disable all
+unnecessary services
+and tasks. Restrict all unnecessary operating system operations.
+
+Remove all
+unnecessary software and
+files.
+
+
+Remove all paging
+space, swap files, partitions, etc.
+
+Shrink your image. (It is recommended to zero all free space and
+reconvert image using qemu-img.)
+
+### Modify your image for running jobs
+
+Your image should run some kind of operating system startup script.
+Startup script should run application and when application exits run
+shutdown or quit virtual machine.
+
+We recommend, that startup script
+
+maps Job Directory from host (from compute node)
+runs script (we call it "run script") from Job Directory and waits for
+application's exit
+- for management purposes if run script does not exist wait for some
+ time period (few minutes)
+
+shutdowns/quits OS
+For Windows operating systems we suggest using Local Group Policy
+Startup script, for Linux operating systems rc.local, runlevel init
+script or similar service.
+
+Example startup script for Windows virtual machine:
+
+ @echo off
+ set LOG=c:startup.log
+ set MAPDRIVE=z:
+ set SCRIPT=%MAPDRIVE%run.bat
+ set TIMEOUT=300
+
+ echo %DATE% %TIME% Running startup script>%LOG%
+
+ rem Mount share
+ echo %DATE% %TIME% Mounting shared drive>%LOG%
+ net use z: 10.0.2.4qemu >%LOG% 2>&1
+ dir z: >%LOG% 2>&1
+ echo. >%LOG%
+
+ if exist %MAPDRIVE% (
+ Â echo %DATE% %TIME% The drive "%MAPDRIVE%" exists>%LOG%
+
+ Â if exist %SCRIPT% (
+ Â Â Â echo %DATE% %TIME% The script file "%SCRIPT%"exists>%LOG%
+ Â Â Â echo %DATE% %TIME% Running script %SCRIPT%>%LOG%
+ Â Â Â set TIMEOUT=0
+ Â Â Â call %SCRIPT%
+ Â ) else (
+ Â Â Â echo %DATE% %TIME% The script file "%SCRIPT%"does not exist>%LOG%
+ Â )
+
+ ) else (
+ Â echo %DATE% %TIME% The drive "%MAPDRIVE%" does not exist>%LOG%
+ )
+ echo. >%LOG%
+
+ timeout /T %TIMEOUT%
+
+ echo %DATE% %TIME% Shut down>%LOG%
+ shutdown /s /t 0
+
+Example startup script maps shared job script as drive z: and looks for
+run script called run.bat. If run script is found it is run else wait
+for 5 minutes, then shutdown virtual machine.
+
+### Create job script for executing virtual machine
+
+Create job script according recommended
+
+[Virtual Machine Job
+Workflow](virtualization.html#virtual-machine-job-workflow).
+
+Example job for Windows virtual machine:
+
+ #/bin/sh
+
+ JOB_DIR=/scratch/$USER/win/${PBS_JOBID}
+
+ #Virtual machine settings
+ VM_IMAGE=~/work/img/win.img
+ VM_MEMORY=49152
+ VM_SMP=16
+
+ # Prepare job dir
+ mkdir -p ${JOB_DIR} && cd ${JOB_DIR} || exit 1
+ ln -s ~/work/win .
+ ln -s /scratch/$USER/data .
+ ln -s ~/work/win/script/run/run-appl.bat run.bat
+
+ # Run virtual machine
+ export TMPDIR=/lscratch/${PBS_JOBID}
+ module add qemu
+ qemu-system-x86_64
+ Â -enable-kvm
+ Â -cpu host
+ Â -smp ${VM_SMP}
+ Â -m ${VM_MEMORY}
+ Â -vga std
+ Â -localtime
+ Â -usb -usbdevice tablet
+ Â -device virtio-net-pci,netdev=net0
+ Â -netdev user,id=net0,smb=${JOB_DIR},hostfwd=tcp::3389-:3389
+ Â -drive file=${VM_IMAGE},media=disk,if=virtio
+ Â -snapshot
+ Â -nographic
+
+Job script links application data (win), input data (data) and run
+script (run.bat) into job directory and runs virtual machine.
+
+Example run script (run.bat) for Windows virtual machine:
+
+ z:
+ cd winappl
+ call application.bat z:data z:output
+
+Run script runs application from shared job directory (mapped as drive
+z:), process input data (z:data) from job directory and store output
+to job directory (z:output).
+
+### Run jobs
+
+Run jobs as usual, see [Resource Allocation and Job
+Execution](../../resource-allocation-and-job-execution/introduction.html).
+Use only full node allocation for virtualization jobs.
+
+### Running Virtual Machines
+
+Virtualization is enabled only on compute nodes, virtualization does not
+work on login nodes.
+
+Load QEMU environment module:
+
+ $ module add qemu
+
+Get help
+
+ $ man qemu
+
+Run virtual machine (simple)
+
+ $ qemu-system-x86_64 -hda linux.img -enable-kvm -cpu host -smp 16 -m 32768 -vga std -vnc :0
+
+ $ qemu-system-x86_64 -hda win.img -enable-kvm -cpu host -smp 16 -m 32768 -vga std -localtime -usb -usbdevice tablet -vnc :0
+
+You can access virtual machine by VNC viewer (option -vnc) connecting to
+IP address of compute node. For VNC you must use [VPN
+network](../../accessing-the-cluster/vpn-access.html).
+
+Install virtual machine from iso file
+
+ $ qemu-system-x86_64 -hda linux.img -enable-kvm -cpu host -smp 16 -m 32768 -vga std -cdrom linux-install.iso -boot d -vnc :0
+
+ $ qemu-system-x86_64 -hda win.img -enable-kvm -cpu host -smp 16 -m 32768 -vga std -localtime -usb -usbdevice tablet -cdrom win-install.iso -boot d -vnc :0
+
+Run virtual machine using optimized devices, user network backend with
+sharing and port forwarding, in snapshot mode
+
+ $ qemu-system-x86_64 -drive file=linux.img,media=disk,if=virtio -enable-kvm -cpu host -smp 16 -m 32768 -vga std -device virtio-net-pci,netdev=net0 -netdev user,id=net0,smb=/scratch/$USER/tmp,hostfwd=tcp::2222-:22 -vnc :0 -snapshot
+
+ $ qemu-system-x86_64 -drive file=win.img,media=disk,if=virtio -enable-kvm -cpu host -smp 16 -m 32768 -vga std -localtime -usb -usbdevice tablet -device virtio-net-pci,netdev=net0 -netdev user,id=net0,smb=/scratch/$USER/tmp,hostfwd=tcp::3389-:3389 -vnc :0 -snapshot
+
+Thanks to port forwarding you can access virtual machine via SSH (Linux)
+or RDP (Windows) connecting to IP address of compute node (and port 2222
+for SSH). You must use [VPN
+network](../../accessing-the-cluster/vpn-access.html).
+
+Keep in mind, that if you use virtio devices, you must have virtio
+drivers installed on your virtual machine.
+
+### Networking and data sharing
+
+For networking virtual machine we suggest to use (default) user network
+backend (sometimes called slirp). This network backend NATs virtual
+machines and provides useful services for virtual machines as DHCP, DNS,
+SMB sharing, port forwarding.
+
+In default configuration IP network 10.0.2.0/24 is used, host has IP
+address 10.0.2.2, DNS server 10.0.2.3, SMB server 10.0.2.4 and virtual
+machines obtain address from range 10.0.2.15-10.0.2.31. Virtual machines
+have access to Anselm's network via NAT on compute node (host).
+
+Simple network setup
+
+ $ qemu-system-x86_64 ... -net nic -net user
+
+(It is default when no -net options are given.)
+
+Simple network setup with sharing and port forwarding (obsolete but
+simpler syntax, lower performance)
+
+ $ qemu-system-x86_64 ... -net nic -net user,smb=/scratch/$USER/tmp,hostfwd=tcp::3389-:3389
+
+Optimized network setup with sharing and port forwarding
+
+ $ qemu-system-x86_64 ... -device virtio-net-pci,netdev=net0 -netdev user,id=net0,smb=/scratch/$USER/tmp,hostfwd=tcp::2222-:22
+
+### Advanced networking
+
+Internet access**
+
+Sometime your virtual machine needs access to internet (install
+software, updates, software activation, etc). We suggest solution using
+Virtual Distributed Ethernet (VDE) enabled QEMU with SLIRP running on
+login node tunnelled to compute node. Be aware, this setup has very low
+performance, the worst performance of all described solutions.
+
+Load VDE enabled QEMU environment module (unload standard QEMU module
+first if necessary).
+
+ $ module add qemu/2.1.2-vde2
+
+Create virtual network switch.
+
+ $ vde_switch -sock /tmp/sw0 -mgmt /tmp/sw0.mgmt -daemon
+
+Run SLIRP daemon over SSH tunnel on login node and connect it to virtual
+network switch.
+
+ $ dpipe vde_plug /tmp/sw0 = ssh login1 $VDE2_DIR/bin/slirpvde -s - --dhcp &
+
+Run qemu using vde network backend, connect to created virtual switch.
+
+Basic setup (obsolete syntax)
+
+ $ qemu-system-x86_64 ... -net nic -net vde,sock=/tmp/sw0
+
+Setup using virtio device (obsolete syntax)
+
+ $ qemu-system-x86_64 ... -net nic,model=virtio -net vde,sock=/tmp/sw0
+
+Optimized setup
+
+ $ qemu-system-x86_64 ... -device virtio-net-pci,netdev=net0 -netdev vde,id=net0,sock=/tmp/sw0
+
+TAP interconnect**
+
+Both user and vde network backend have low performance. For fast
+interconnect (10Gbps and more) of compute node (host) and virtual
+machine (guest) we suggest using Linux kernel TAP device.
+
+Cluster Anselm provides TAP device tap0 for your job. TAP interconnect
+does not provide any services (like NAT, DHCP, DNS, SMB, etc.) just raw
+networking, so you should provide your services if you need them.
+
+Run qemu with TAP network backend:
+
+ $ qemu-system-x86_64 ... -device virtio-net-pci,netdev=net1
+ -netdev tap,id=net1,ifname=tap0,script=no,downscript=no
+
+Interface tap0 has IP address 192.168.1.1 and network mask 255.255.255.0
+(/24). In virtual machine use IP address from range
+192.168.1.2-192.168.1.254. For your convenience some ports on tap0
+interface are redirected to higher numbered ports, so you as
+non-privileged user can provide services on these ports.
+
+Redirected ports:
+
+- DNS udp/53->udp/3053, tcp/53->tcp3053
+- DHCP udp/67->udp3067
+- SMB tcp/139->tcp3139, tcp/445->tcp3445).
+
+You can configure IP address of virtual machine statically or
+dynamically. For dynamic addressing provide your DHCP server on port
+3067 of tap0 interface, you can also provide your DNS server on port
+3053 of tap0 interface for example:
+
+ $ dnsmasq --interface tap0 --bind-interfaces -p 3053 --dhcp-alternate-port=3067,68 --dhcp-range=192.168.1.15,192.168.1.32 --dhcp-leasefile=/tmp/dhcp.leasefile
+
+You can also provide your SMB services (on ports 3139, 3445) to obtain
+high performance data sharing.
+
+Example smb.conf (not optimized)
+
+ [global]
+ socket address=192.168.1.1
+ smb ports = 3445 3139
+
+ private dir=/tmp/qemu-smb
+ pid directory=/tmp/qemu-smb
+ lock directory=/tmp/qemu-smb
+ state directory=/tmp/qemu-smb
+ ncalrpc dir=/tmp/qemu-smb/ncalrpc
+ log file=/tmp/qemu-smb/log.smbd
+ smb passwd file=/tmp/qemu-smb/smbpasswd
+ security = user
+ map to guest = Bad User
+ unix extensions = no
+ load printers = no
+ printing = bsd
+ printcap name = /dev/null
+ disable spoolss = yes
+ log level = 1
+ guest account = USER
+ [qemu]
+ path=/scratch/USER/tmp
+ read only=no
+ guest ok=yes
+ writable=yes
+ follow symlinks=yes
+ wide links=yes
+ force user=USER
+
+(Replace USER with your login name.)
+
+Run SMB services
+
+ smbd -s /tmp/qemu-smb/smb.conf
+
+Â
+
+Virtual machine can of course have more than one network interface
+controller, virtual machine can use more than one network backend. So,
+you can combine for example use network backend and TAP interconnect.
+
+### Snapshot mode
+
+In snapshot mode image is not written, changes are written to temporary
+file (and discarded after virtual machine exits). **It is strongly
+recommended mode for running your jobs.** Set TMPDIR environment
+variable to local scratch directory for placement temporary files.
+
+ $ export TMPDIR=/lscratch/${PBS_JOBID}
+ $ qemu-system-x86_64 ... -snapshot
+
+### Windows guests
+
+For Windows guests we recommend these options, life will be easier:
+
+ $ qemu-system-x86_64 ... -localtime -usb -usbdevice tablet
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/mpi-1/Running_OpenMPI.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/mpi-1/Running_OpenMPI.md
new file mode 100644
index 0000000000000000000000000000000000000000..03477ba6e3b3ecd0b61b5086adb72f431dfc91b1
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/mpi-1/Running_OpenMPI.md
@@ -0,0 +1,242 @@
+Running OpenMPI
+===============
+
+
+
+OpenMPI program execution
+-------------------------
+
+The OpenMPI programs may be executed only via the PBS Workload manager,
+by entering an appropriate queue. On Anselm, the **bullxmpi-1.2.4.1**
+and **OpenMPI 1.6.5** are OpenMPI based MPI implementations.
+
+### Basic usage
+
+Use the mpiexec to run the OpenMPI code.
+
+Example:
+
+ $ qsub -q qexp -l select=4:ncpus=16 -I
+ qsub: waiting for job 15210.srv11 to start
+ qsub: job 15210.srv11 ready
+
+ $ pwd
+ /home/username
+
+ $ module load openmpi
+ $ mpiexec -pernode ./helloworld_mpi.x
+ Hello world! from rank 0 of 4 on host cn17
+ Hello world! from rank 1 of 4 on host cn108
+ Hello world! from rank 2 of 4 on host cn109
+ Hello world! from rank 3 of 4 on host cn110
+
+Please be aware, that in this example, the directive **-pernode** is
+used to run only **one task per node**, which is normally an unwanted
+behaviour (unless you want to run hybrid code with just one MPI and 16
+OpenMP tasks per node). In normal MPI programs **omit the -pernode
+directive** to run up to 16 MPI tasks per each node.
+
+In this example, we allocate 4 nodes via the express queue
+interactively. We set up the openmpi environment and interactively run
+the helloworld_mpi.x program.
+Note that the executable
+helloworld_mpi.x must be available within the
+same path on all nodes. This is automatically fulfilled on the /home and
+/scratch filesystem.
+
+You need to preload the executable, if running on the local scratch
+/lscratch filesystem
+
+ $ pwd
+ /lscratch/15210.srv11
+
+ $ mpiexec -pernode --preload-binary ./helloworld_mpi.x
+ Hello world! from rank 0 of 4 on host cn17
+ Hello world! from rank 1 of 4 on host cn108
+ Hello world! from rank 2 of 4 on host cn109
+ Hello world! from rank 3 of 4 on host cn110
+
+In this example, we assume the executable
+helloworld_mpi.x is present on compute node
+cn17 on local scratch. We call the mpiexec whith the
+--preload-binary** argument (valid for openmpi). The mpiexec will copy
+the executable from cn17 to the
+/lscratch/15210.srv11 directory on cn108, cn109
+and cn110 and execute the program.
+
+MPI process mapping may be controlled by PBS parameters.
+
+The mpiprocs and ompthreads parameters allow for selection of number of
+running MPI processes per node as well as number of OpenMP threads per
+MPI process.
+
+### One MPI process per node
+
+Follow this example to run one MPI process per node, 16 threads per
+process.Â
+
+ $ qsub -q qexp -l select=4:ncpus=16:mpiprocs=1:ompthreads=16 -I
+
+ $ module load openmpi
+
+ $ mpiexec --bind-to-none ./helloworld_mpi.x
+
+In this example, we demonstrate recommended way to run an MPI
+application, using 1 MPI processes per node and 16 threads per socket,
+on 4 nodes.
+
+### Two MPI processes per node
+
+Follow this example to run two MPI processes per node, 8 threads per
+process. Note the options to mpiexec.
+
+ $ qsub -q qexp -l select=4:ncpus=16:mpiprocs=2:ompthreads=8 -I
+
+ $ module load openmpi
+
+ $ mpiexec -bysocket -bind-to-socket ./helloworld_mpi.x
+
+In this example, we demonstrate recommended way to run an MPI
+application, using 2 MPI processes per node and 8 threads per socket,
+each process and its threads bound to a separate processor socket of the
+node, on 4 nodes
+
+### 16 MPI processes per node
+
+Follow this example to run 16 MPI processes per node, 1 thread per
+process. Note the options to mpiexec.
+
+ $ qsub -q qexp -l select=4:ncpus=16:mpiprocs=16:ompthreads=1 -I
+
+ $ module load openmpi
+
+ $ mpiexec -bycore -bind-to-core ./helloworld_mpi.x
+
+In this example, we demonstrate recommended way to run an MPI
+application, using 16 MPI processes per node, single threaded. Each
+process is bound to separate processor core, on 4 nodes.
+
+### OpenMP thread affinity
+
+Important! Bind every OpenMP thread to a core!
+
+In the previous two examples with one or two MPI processes per node, the
+operating system might still migrate OpenMP threads between cores. You
+might want to avoid this by setting these environment variable for GCC
+OpenMP:
+
+ $ export GOMP_CPU_AFFINITY="0-15"
+
+or this one for Intel OpenMP:
+
+ $ export KMP_AFFINITY=granularity=fine,compact,1,0
+
+As of OpenMP 4.0 (supported by GCC 4.9 and later and Intel 14.0 and
+later) the following variables may be used for Intel or GCC:
+
+ $ export OMP_PROC_BIND=true
+ $ export OMP_PLACES=coresÂ
+
+OpenMPI Process Mapping and Binding
+------------------------------------------------
+
+The mpiexec allows for precise selection of how the MPI processes will
+be mapped to the computational nodes and how these processes will bind
+to particular processor sockets and cores.
+
+MPI process mapping may be specified by a hostfile or rankfile input to
+the mpiexec program. Altough all implementations of MPI provide means
+for process mapping and binding, following examples are valid for the
+openmpi only.
+
+### Hostfile
+
+Example hostfile
+
+ cn110.bullx
+ cn109.bullx
+ cn108.bullx
+ cn17.bullx
+
+Use the hostfile to control process placement
+
+ $ mpiexec -hostfile hostfile ./helloworld_mpi.x
+ Hello world! from rank 0 of 4 on host cn110
+ Hello world! from rank 1 of 4 on host cn109
+ Hello world! from rank 2 of 4 on host cn108
+ Hello world! from rank 3 of 4 on host cn17
+
+In this example, we see that ranks have been mapped on nodes according
+to the order in which nodes show in the hostfile
+
+### Rankfile
+
+Exact control of MPI process placement and resource binding is provided
+by specifying a rankfile
+
+Appropriate binding may boost performance of your application.
+
+Example rankfile
+
+ rank 0=cn110.bullx slot=1:0,1
+ rank 1=cn109.bullx slot=0:*
+ rank 2=cn108.bullx slot=1:1-2
+ rank 3=cn17.bullx slot=0:1,1:0-2
+ rank 4=cn109.bullx slot=0:*,1:*
+
+This rankfile assumes 5 ranks will be running on 4 nodes and provides
+exact mapping and binding of the processes to the processor sockets and
+cores
+
+Explanation:
+rank 0 will be bounded to cn110, socket1 core0 and core1
+rank 1 will be bounded to cn109, socket0, all cores
+rank 2 will be bounded to cn108, socket1, core1 and core2
+rank 3 will be bounded to cn17, socket0 core1, socket1 core0, core1,
+core2
+rank 4 will be bounded to cn109, all cores on both sockets
+
+ $ mpiexec -n 5 -rf rankfile --report-bindings ./helloworld_mpi.x
+ [cn17:11180] MCW rank 3 bound to socket 0[core 1] socket 1[core 0-2]: [. B . . . . . .][B B B . . . . .] (slot list 0:1,1:0-2)
+ [cn110:09928] MCW rank 0 bound to socket 1[core 0-1]: [. . . . . . . .][B B . . . . . .] (slot list 1:0,1)
+ [cn109:10395] MCW rank 1 bound to socket 0[core 0-7]: [B B B B B B B B][. . . . . . . .] (slot list 0:*)
+ [cn108:10406] MCW rank 2 bound to socket 1[core 1-2]: [. . . . . . . .][. B B . . . . .] (slot list 1:1-2)
+ [cn109:10406] MCW rank 4 bound to socket 0[core 0-7] socket 1[core 0-7]: [B B B B B B B B][B B B B B B B B] (slot list 0:*,1:*)
+ Hello world! from rank 3 of 5 on host cn17
+ Hello world! from rank 1 of 5 on host cn109
+ Hello world! from rank 0 of 5 on host cn110
+ Hello world! from rank 4 of 5 on host cn109
+ Hello world! from rank 2 of 5 on host cn108
+
+In this example we run 5 MPI processes (5 ranks) on four nodes. The
+rankfile defines how the processes will be mapped on the nodes, sockets
+and cores. The **--report-bindings** option was used to print out the
+actual process location and bindings. Note that ranks 1 and 4 run on the
+same node and their core binding overlaps.
+
+It is users responsibility to provide correct number of ranks, sockets
+and cores.
+
+### Bindings verification
+
+In all cases, binding and threading may be verified by executing for
+example:
+
+ $ mpiexec -bysocket -bind-to-socket --report-bindings echo
+ $ mpiexec -bysocket -bind-to-socket numactl --show
+ $ mpiexec -bysocket -bind-to-socket echo $OMP_NUM_THREADS
+
+Changes in OpenMPI 1.8
+----------------------
+
+Some options have changed in OpenMPI version 1.8.
+
+ |version 1.6.5 |version 1.8.1 |
+ | --- | --- |
+ |--bind-to-none |--bind-to none |
+ |--bind-to-core |--bind-to core |
+ |--bind-to-socket |--bind-to socket |
+ |-bysocket |--map-by socket |
+ |-bycore |--map-by core |
+ |-pernode |--map-by ppr:1:node\ |
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/mpi-1/mpi.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/mpi-1/mpi.md
new file mode 100644
index 0000000000000000000000000000000000000000..fb348bb0091106d09774641c992a2f6ecca9cd56
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/mpi-1/mpi.md
@@ -0,0 +1,171 @@
+MPI
+===
+
+
+
+Setting up MPI Environment
+--------------------------
+
+The Anselm cluster provides several implementations of the MPI library:
+
+ |MPI Library |Thread support |
+ | --- | --- |
+ |The highly optimized and stable <strong>bullxmpi 1.2.4.1</strong>\ |<strong></strong>Partial thread support up to MPI_THREAD_SERIALIZED |
+ |The <strong>Intel MPI 4.1</strong> |Full thread support up to MPI_THREAD_MULTIPLE |
+ |The <a href="http://www.open-mpi.org/" <strong>OpenMPI 1.6.5</strong></a> |Full thread support up to MPI_THREAD_MULTIPLE, BLCR c/r support |
+ |The OpenMPI 1.8.1 |Full thread support up to MPI_THREAD_MULTIPLE, MPI-3.0 support |
+ |The <strong><strong>mpich2 1.9</strong></strong> |Full thread support up to <strong></strong> MPI_THREAD_MULTIPLE, BLCR c/r support |
+
+MPI libraries are activated via the environment modules.
+
+Look up section modulefiles/mpi in module avail
+
+ $ module avail
+ ------------------------- /opt/modules/modulefiles/mpi -------------------------
+ bullxmpi/bullxmpi-1.2.4.1 mvapich2/1.9-icc
+ impi/4.0.3.008 openmpi/1.6.5-gcc(default)
+ impi/4.1.0.024 openmpi/1.6.5-gcc46
+ impi/4.1.0.030 openmpi/1.6.5-icc
+ impi/4.1.1.036(default) openmpi/1.8.1-gcc
+ openmpi/1.8.1-gcc46
+ mvapich2/1.9-gcc(default) openmpi/1.8.1-gcc49
+ mvapich2/1.9-gcc46 openmpi/1.8.1-icc
+
+There are default compilers associated with any particular MPI
+implementation. The defaults may be changed, the MPI libraries may be
+used in conjunction with any compiler.
+The defaults are selected via the modules in following way
+
+ Module MPI Compiler suite
+ -------- |---|---|-------- --------------------------------------------------------------------------------
+ PrgEnv-gnu bullxmpi-1.2.4.1 bullx GNU 4.4.6
+ PrgEnv-intel Intel MPI 4.1.1 Intel 13.1.1
+ bullxmpi bullxmpi-1.2.4.1 none, select via module
+ impi Intel MPI 4.1.1 none, select via module
+ openmpi OpenMPI 1.6.5 GNU compilers 4.8.1, GNU compilers 4.4.6, Intel Compilers
+ openmpi OpenMPI 1.8.1 GNU compilers 4.8.1, GNU compilers 4.4.6, GNU compilers 4.9.0, Intel Compilers
+ mvapich2 MPICH2 1.9 GNU compilers 4.8.1, GNU compilers 4.4.6, Intel Compilers
+
+Examples:
+
+ $ module load openmpi
+
+In this example, we activate the latest openmpi with latest GNU
+compilers
+
+To use openmpi with the intel compiler suite, use
+
+ $ module load intel
+ $ module load openmpi/1.6.5-icc
+
+In this example, the openmpi 1.6.5 using intel compilers is activated
+
+Compiling MPI Programs
+----------------------
+
+After setting up your MPI environment, compile your program using one of
+the mpi wrappers
+
+ $ mpicc -v
+ $ mpif77 -v
+ $ mpif90 -v
+
+Example program:
+
+ // helloworld_mpi.c
+ #include <stdio.h>
+
+ #include<mpi.h>
+
+ int main(int argc, char **argv) {
+
+ int len;
+ int rank, size;
+ char node[MPI_MAX_PROCESSOR_NAME];
+
+ // Initiate MPI
+ MPI_Init(&argc, &argv);
+ MPI_Comm_rank(MPI_COMM_WORLD,&rank);
+ MPI_Comm_size(MPI_COMM_WORLD,&size);
+
+ // Get hostame and print
+ MPI_Get_processor_name(node,&len);
+ printf("Hello world! from rank %d of %d on host %sn",rank,size,node);
+
+ // Finalize and exit
+ MPI_Finalize();
+
+ return 0;
+ }
+
+Compile the above example with
+
+ $ mpicc helloworld_mpi.c -o helloworld_mpi.x
+
+Running MPI Programs
+--------------------
+
+The MPI program executable must be compatible with the loaded MPI
+module.
+Always compile and execute using the very same MPI module.
+
+It is strongly discouraged to mix mpi implementations. Linking an
+application with one MPI implementation and running mpirun/mpiexec form
+other implementation may result in unexpected errors.
+
+The MPI program executable must be available within the same path on all
+nodes. This is automatically fulfilled on the /home and /scratch
+filesystem. You need to preload the executable, if running on the local
+scratch /lscratch filesystem.
+
+### Ways to run MPI programs
+
+Optimal way to run an MPI program depends on its memory requirements,
+memory access pattern and communication pattern.
+
+Consider these ways to run an MPI program:
+1. One MPI process per node, 16 threads per process
+2. Two MPI processes per node, 8 threads per process
+3. 16 MPI processes per node, 1 thread per process.
+
+One MPI** process per node, using 16 threads, is most useful for
+memory demanding applications, that make good use of processor cache
+memory and are not memory bound. This is also a preferred way for
+communication intensive applications as one process per node enjoys full
+bandwidth access to the network interface.Â
+
+Two MPI** processes per node, using 8 threads each, bound to processor
+socket is most useful for memory bandwidth bound applications such as
+BLAS1 or FFT, with scalable memory demand. However, note that the two
+processes will share access to the network interface. The 8 threads and
+socket binding should ensure maximum memory access bandwidth and
+minimize communication, migration and numa effect overheads.
+
+Important! Bind every OpenMP thread to a core!
+
+In the previous two cases with one or two MPI processes per node, the
+operating system might still migrate OpenMP threads between cores. You
+want to avoid this by setting the KMP_AFFINITY or GOMP_CPU_AFFINITY
+environment variables.
+
+16 MPI** processes per node, using 1 thread each bound to processor
+core is most suitable for highly scalable applications with low
+communication demand.
+
+### Running OpenMPI
+
+The **bullxmpi-1.2.4.1** and [**OpenMPI
+1.6.5**](http://www.open-mpi.org/) are both based on
+OpenMPI. Read more on [how to run
+OpenMPI](Running_OpenMPI.html) based MPI.
+
+### Running MPICH2
+
+The **Intel MPI** and **mpich2 1.9** are MPICH2 based implementations.
+Read more on [how to run MPICH2](running-mpich2.html)
+based MPI.
+
+The Intel MPI may run on the Intel Xeon Phi accelerators as well. Read
+more on [how to run Intel MPI on
+accelerators](../intel-xeon-phi.html).
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/mpi-1/mpi4py-mpi-for-python.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/mpi-1/mpi4py-mpi-for-python.md
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+MPI4Py (MPI for Python)
+=======================
+
+OpenMPI interface to Python
+
+
+
+Introduction
+------------
+
+MPI for Python provides bindings of the Message Passing Interface (MPI)
+standard for the Python programming language, allowing any Python
+program to exploit multiple processors.
+
+This package is constructed on top of the MPI-1/2 specifications and
+provides an object oriented interface which closely follows MPI-2 C++
+bindings. It supports point-to-point (sends, receives) and collective
+(broadcasts, scatters, gathers) communications of any picklable Python
+object, as well as optimized communications of Python object exposing
+the single-segment buffer interface (NumPy arrays, builtin
+bytes/string/array objects).
+
+On Anselm MPI4Py is available in standard Python modules.
+
+Modules
+-------
+
+MPI4Py is build for OpenMPI. Before you start with MPI4Py you need to
+load Python and OpenMPI modules.
+
+ $ module load python
+ $ module load openmpi
+
+Execution
+---------
+
+You need to import MPI to your python program. Include the following
+line to the python script:
+
+ from mpi4py import MPI
+
+The MPI4Py enabled python programs [execute as any other
+OpenMPI](Running_OpenMPI.html) code.The simpliest way is
+to run
+
+ $ mpiexec python <script>.py
+
+For example
+
+ $ mpiexec python hello_world.py
+
+Examples
+--------
+
+### Hello world!
+
+ from mpi4py import MPI
+
+ comm = MPI.COMM_WORLD
+
+ print "Hello! I'm rank %d from %d running in total..." % (comm.rank, comm.size)
+
+ comm.Barrier() Â # wait for everybody to synchronize
+
+###Collective Communication with NumPy arrays
+
+ from mpi4py import MPI
+ from __future__ import division
+ import numpy as np
+
+ comm = MPI.COMM_WORLD
+
+ print("-"*78)
+ print(" Running on %d cores" % comm.size)
+ print("-"*78)
+
+ comm.Barrier()
+
+ # Prepare a vector of N=5 elements to be broadcasted...
+ N = 5
+ if comm.rank == 0:
+ Â Â A = np.arange(N, dtype=np.float64) Â Â # rank 0 has proper data
+ else:
+ Â Â A = np.empty(N, dtype=np.float64) Â Â # all other just an empty array
+
+ # Broadcast A from rank 0 to everybody
+ comm.Bcast( [A, MPI.DOUBLE] )
+
+ # Everybody should now have the same...
+ print "[%02d] %s" % (comm.rank, A)
+
+Execute the above code as:
+
+ $ qsub -q qexp -l select=4:ncpus=16:mpiprocs=16:ompthreads=1 -I
+
+ $ module load python openmpi
+
+ $ mpiexec -bycore -bind-to-core python hello_world.py
+
+In this example, we run MPI4Py enabled code on 4 nodes, 16 cores per
+node (total of 64 processes), each python process is bound to a
+different core.
+More examples and documentation can be found on [MPI for Python
+webpage](https://pythonhosted.org/mpi4py/usrman/index.html).
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/mpi-1/running-mpich2.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/mpi-1/running-mpich2.md
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+Running MPICH2
+==============
+
+
+
+MPICH2 program execution
+------------------------
+
+The MPICH2 programs use mpd daemon or ssh connection to spawn processes,
+no PBS support is needed. However the PBS allocation is required to
+access compute nodes. On Anselm, the **Intel MPI** and **mpich2 1.9**
+are MPICH2 based MPI implementations.
+
+### Basic usage
+
+Use the mpirun to execute the MPICH2 code.
+
+Example:
+
+ $ qsub -q qexp -l select=4:ncpus=16 -I
+ qsub: waiting for job 15210.srv11 to start
+ qsub: job 15210.srv11 ready
+
+ $ module load impi
+
+ $ mpirun -ppn 1 -hostfile $PBS_NODEFILE ./helloworld_mpi.x
+ Hello world! from rank 0 of 4 on host cn17
+ Hello world! from rank 1 of 4 on host cn108
+ Hello world! from rank 2 of 4 on host cn109
+ Hello world! from rank 3 of 4 on host cn110
+
+In this example, we allocate 4 nodes via the express queue
+interactively. We set up the intel MPI environment and interactively run
+the helloworld_mpi.x program. We request MPI to spawn 1 process per
+node.
+Note that the executable helloworld_mpi.x must be available within the
+same path on all nodes. This is automatically fulfilled on the /home and
+/scratch filesystem.
+
+You need to preload the executable, if running on the local scratch
+/lscratch filesystem
+
+ $ pwd
+ /lscratch/15210.srv11
+ $ mpirun -ppn 1 -hostfile $PBS_NODEFILE cp /home/username/helloworld_mpi.x .
+ $ mpirun -ppn 1 -hostfile $PBS_NODEFILE ./helloworld_mpi.x
+ Hello world! from rank 0 of 4 on host cn17
+ Hello world! from rank 1 of 4 on host cn108
+ Hello world! from rank 2 of 4 on host cn109
+ Hello world! from rank 3 of 4 on host cn110
+
+In this example, we assume the executable helloworld_mpi.x is present
+on shared home directory. We run the cp command via mpirun, copying the
+executable from shared home to local scratch . Second mpirun will
+execute the binary in the /lscratch/15210.srv11 directory on nodes cn17,
+cn108, cn109 and cn110, one process per node.
+
+MPI process mapping may be controlled by PBS parameters.
+
+The mpiprocs and ompthreads parameters allow for selection of number of
+running MPI processes per node as well as number of OpenMP threads per
+MPI process.
+
+### One MPI process per node
+
+Follow this example to run one MPI process per node, 16 threads per
+process. Note that no options to mpirun are needed
+
+ $ qsub -q qexp -l select=4:ncpus=16:mpiprocs=1:ompthreads=16 -I
+
+ $ module load mvapich2
+
+ $ mpirun ./helloworld_mpi.x
+
+In this example, we demonstrate recommended way to run an MPI
+application, using 1 MPI processes per node and 16 threads per socket,
+on 4 nodes.
+
+### Two MPI processes per node
+
+Follow this example to run two MPI processes per node, 8 threads per
+process. Note the options to mpirun for mvapich2. No options are needed
+for impi.
+
+ $ qsub -q qexp -l select=4:ncpus=16:mpiprocs=2:ompthreads=8 -I
+
+ $ module load mvapich2
+
+ $ mpirun -bind-to numa ./helloworld_mpi.x
+
+In this example, we demonstrate recommended way to run an MPI
+application, using 2 MPI processes per node and 8 threads per socket,
+each process and its threads bound to a separate processor socket of the
+node, on 4 nodes
+
+### 16 MPI processes per node
+
+Follow this example to run 16 MPI processes per node, 1 thread per
+process. Note the options to mpirun for mvapich2. No options are needed
+for impi.
+
+ $ qsub -q qexp -l select=4:ncpus=16:mpiprocs=16:ompthreads=1 -I
+
+ $ module load mvapich2
+
+ $ mpirun -bind-to core ./helloworld_mpi.x
+
+In this example, we demonstrate recommended way to run an MPI
+application, using 16 MPI processes per node, single threaded. Each
+process is bound to separate processor core, on 4 nodes.
+
+### OpenMP thread affinity
+
+Important! Bind every OpenMP thread to a core!
+
+In the previous two examples with one or two MPI processes per node, the
+operating system might still migrate OpenMP threads between cores. You
+might want to avoid this by setting these environment variable for GCC
+OpenMP:
+
+ $ export GOMP_CPU_AFFINITY="0-15"
+
+or this one for Intel OpenMP:
+
+ $ export KMP_AFFINITY=granularity=fine,compact,1,0
+
+As of OpenMP 4.0 (supported by GCC 4.9 and later and Intel 14.0 and
+later) the following variables may be used for Intel or GCC:
+
+ $ export OMP_PROC_BIND=true
+ $ export OMP_PLACES=cores
+
+Â
+
+MPICH2 Process Mapping and Binding
+----------------------------------
+
+The mpirun allows for precise selection of how the MPI processes will be
+mapped to the computational nodes and how these processes will bind to
+particular processor sockets and cores.
+
+### Machinefile
+
+Process mapping may be controlled by specifying a machinefile input to
+the mpirun program. Altough all implementations of MPI provide means for
+process mapping and binding, following examples are valid for the impi
+and mvapich2 only.
+
+Example machinefile
+
+ cn110.bullx
+ cn109.bullx
+ cn108.bullx
+ cn17.bullx
+ cn108.bullx
+
+Use the machinefile to control process placement
+
+ $ mpirun -machinefile machinefile helloworld_mpi.x
+ Hello world! from rank 0 of 5 on host cn110
+ Hello world! from rank 1 of 5 on host cn109
+ Hello world! from rank 2 of 5 on host cn108
+ Hello world! from rank 3 of 5 on host cn17
+ Hello world! from rank 4 of 5 on host cn108
+
+In this example, we see that ranks have been mapped on nodes according
+to the order in which nodes show in the machinefile
+
+### Process Binding
+
+The Intel MPI automatically binds each process and its threads to the
+corresponding portion of cores on the processor socket of the node, no
+options needed. The binding is primarily controlled by environment
+variables. Read more about mpi process binding on [Intel
+website](https://software.intel.com/sites/products/documentation/hpc/ics/impi/41/lin/Reference_Manual/Environment_Variables_Process_Pinning.htm).
+The MPICH2 uses the -bind-to option Use -bind-to numa or -bind-to core
+to bind the process on single core or entire socket.
+
+### Bindings verification
+
+In all cases, binding and threading may be verified by executing
+
+ $ mpirun -bindto numa numactl --show
+ $ mpirun -bindto numa echo $OMP_NUM_THREADS
+
+Intel MPI on Xeon Phi
+---------------------
+
+The[MPI section of Intel Xeon Phi
+chapter](../intel-xeon-phi.html) provides details on how
+to run Intel MPI code on Xeon Phi architecture.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/Matlab.png b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/Matlab.png
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diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/copy_of_matlab.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/copy_of_matlab.md
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+Matlab
+======
+
+
+
+Introduction
+------------
+
+Matlab is available in versions R2015a and R2015b. There are always two
+variants of the release:
+
+- Non commercial or so called EDU variant, which can be used for
+ common research and educational purposes.
+- Commercial or so called COM variant, which can used also for
+ commercial activities. The licenses for commercial variant are much
+ more expensive, so usually the commercial variant has only subset of
+ features compared to the EDU available.
+
+Â
+
+To load the latest version of Matlab load the module
+
+ $ module load MATLAB
+
+By default the EDU variant is marked as default. If you need other
+version or variant, load the particular version. To obtain the list of
+available versions use
+
+ $ module avail MATLAB
+
+If you need to use the Matlab GUI to prepare your Matlab programs, you
+can use Matlab directly on the login nodes. But for all computations use
+Matlab on the compute nodes via PBS Pro scheduler.
+
+If you require the Matlab GUI, please follow the general informations
+about [running graphical
+applications](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html).
+
+Matlab GUI is quite slow using the X forwarding built in the PBS (qsub
+-X), so using X11 display redirection either via SSH or directly by
+xauth (please see the "GUI Applications on Compute Nodes over VNC" part
+[here](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html))
+is recommended.
+
+To run Matlab with GUI, use
+
+ $ matlab
+
+To run Matlab in text mode, without the Matlab Desktop GUI environment,
+use
+
+ $ matlab -nodesktop -nosplash
+
+plots, images, etc... will be still available.
+
+Running parallel Matlab using Distributed Computing Toolbox / Engine
+------------------------------------------------------------------------
+
+Distributed toolbox is available only for the EDU variant
+
+The MPIEXEC mode available in previous versions is no longer available
+in MATLAB 2015. Also, the programming interface has changed. Refer
+to [Release
+Notes](http://www.mathworks.com/help/distcomp/release-notes.html#buanp9e-1).
+
+Delete previously used file mpiLibConf.m, we have observed crashes when
+using Intel MPI.
+
+To use Distributed Computing, you first need to setup a parallel
+profile. We have provided the profile for you, you can either import it
+in MATLAB command line:
+
+ > parallel.importProfile('/apps/all/MATLAB/2015a-EDU/SalomonPBSPro.settings')
+
+ ans =
+
+ SalomonPBSProÂ
+
+Or in the GUI, go to tab HOME -> Parallel -> Manage Cluster
+Profiles..., click Import and navigate to :
+
+/apps/all/MATLAB/2015a-EDU/SalomonPBSPro.settings
+
+With the new mode, MATLAB itself launches the workers via PBS, so you
+can either use interactive mode or a batch mode on one node, but the
+actual parallel processing will be done in a separate job started by
+MATLAB itself. Alternatively, you can use "local" mode to run parallel
+code on just a single node.
+
+The profile is confusingly named Salomon, but you can use it also on
+Anselm.
+
+### Parallel Matlab interactive session
+
+Following example shows how to start interactive session with support
+for Matlab GUI. For more information about GUI based applications on
+Anselm see [this
+page](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html).
+
+ $ xhost +
+ $ qsub -I -v DISPLAY=$(uname -n):$(echo $DISPLAY | cut -d ':' -f 2) -A NONE-0-0 -q qexp -l select=1 -l walltime=00:30:00
+ -l feature__matlab__MATLAB=1
+
+This qsub command example shows how to run Matlab on a single node.
+
+The second part of the command shows how to request all necessary
+licenses. In this case 1 Matlab-EDU license and 48 Distributed Computing
+Engines licenses.
+
+Once the access to compute nodes is granted by PBS, user can load
+following modules and start Matlab:Â
+
+ r1i0n17$ module load MATLAB/2015b-EDU
+ r1i0n17$ matlab &
+
+### Parallel Matlab batch job in Local mode
+
+To run matlab in batch mode, write an matlab script, then write a bash
+jobscript and execute via the qsub command. By default, matlab will
+execute one matlab worker instance per allocated core.
+
+ #!/bin/bash
+ #PBS -A PROJECT ID
+ #PBS -q qprod
+ #PBS -l select=1:ncpus=16:mpiprocs=16:ompthreads=1
+
+ # change to shared scratch directory
+ SCR=/scratch/work/user/$USER/$PBS_JOBID
+ mkdir -p $SCR ; cd $SCR || exit
+
+ # copy input file to scratch
+ cp $PBS_O_WORKDIR/matlabcode.m .
+
+ # load modules
+ module load MATLAB/2015a-EDU
+
+ # execute the calculation
+ matlab -nodisplay -r matlabcode > output.out
+
+ # copy output file to home
+ cp output.out $PBS_O_WORKDIR/.
+
+This script may be submitted directly to the PBS workload manager via
+the qsub command. The inputs and matlab script are in matlabcode.m
+file, outputs in output.out file. Note the missing .m extension in the
+matlab -r matlabcodefile call, **the .m must not be included**. Note
+that the **shared /scratch must be used**. Further, it is **important to
+include quit** statement at the end of the matlabcode.m script.
+
+Submit the jobscript using qsub
+
+ $ qsub ./jobscript
+
+### Parallel Matlab Local mode program example
+
+The last part of the configuration is done directly in the user Matlab
+script before Distributed Computing Toolbox is started.
+
+ cluster = parcluster('local')
+
+This script creates scheduler object "cluster" of type "local" that
+starts workers locally.Â
+
+Please note: Every Matlab script that needs to initialize/use matlabpool
+has to contain these three lines prior to calling parpool(sched, ...)
+function.Â
+
+The last step is to start matlabpool with "cluster" object and correct
+number of workers. We have 24 cores per node, so we start 24 workers.
+
+ parpool(cluster,16);
+
+
+ ... parallel code ...
+
+
+ parpool close
+
+The complete example showing how to use Distributed Computing Toolbox in
+local mode is shown here.Â
+
+ cluster = parcluster('local');
+ cluster
+
+ parpool(cluster,24);
+
+ n=2000;
+
+ W = rand(n,n);
+ W = distributed(W);
+ x = (1:n)';
+ x = distributed(x);
+ spmd
+ [~, name] = system('hostname')
+ Â Â Â
+ Â Â Â T = W*x; % Calculation performed on labs, in parallel.
+ Â Â Â Â Â Â Â Â Â Â Â Â % T and W are both codistributed arrays here.
+ end
+ T;
+ whos        % T and W are both distributed arrays here.
+
+ parpool close
+ quit
+
+You can copy and paste the example in a .m file and execute. Note that
+the parpool size should correspond to **total number of cores**
+available on allocated nodes.
+
+### Parallel Matlab Batch job using PBS mode (workers spawned in a separate job)
+
+This mode uses PBS scheduler to launch the parallel pool. It uses the
+SalomonPBSPro profile that needs to be imported to Cluster Manager, as
+mentioned before. This methodod uses MATLAB's PBS Scheduler interface -
+it spawns the workers in a separate job submitted by MATLAB using qsub.
+
+This is an example of m-script using PBS mode:
+
+ cluster = parcluster('SalomonPBSPro');
+ set(cluster, 'SubmitArguments', '-A OPEN-0-0');
+ set(cluster, 'ResourceTemplate', '-q qprod -l select=10:ncpus=16');
+ set(cluster, 'NumWorkers', 160);
+
+ pool = parpool(cluster, 160);
+
+ n=2000;
+
+ W = rand(n,n);
+ W = distributed(W);
+ x = (1:n)';
+ x = distributed(x);
+ spmd
+ [~, name] = system('hostname')
+
+ T = W*x; % Calculation performed on labs, in parallel.
+ % T and W are both codistributed arrays here.
+ end
+ whos % T and W are both distributed arrays here.
+
+ % shut down parallel pool
+ delete(pool)
+
+Note that we first construct a cluster object using the imported
+profile, then set some important options, namely : SubmitArguments,
+where you need to specify accounting id, and ResourceTemplate, where you
+need to specify number of nodes to run the job.Â
+
+You can start this script using batch mode the same way as in Local mode
+example.
+
+### Parallel Matlab Batch with direct launch (workers spawned within the existing job)
+
+This method is a "hack" invented by us to emulate the mpiexec
+functionality found in previous MATLAB versions. We leverage the MATLAB
+Generic Scheduler interface, but instead of submitting the workers to
+PBS, we launch the workers directly within the running job, thus we
+avoid the issues with master script and workers running in separate jobs
+(issues with license not available, waiting for the worker's job to
+spawn etc.)
+
+Please note that this method is experimental.
+
+For this method, you need to use SalomonDirect profile, import it
+using [the same way as
+SalomonPBSPro](copy_of_matlab.html#running-parallel-matlab-using-distributed-computing-toolbox---engine)Â
+
+This is an example of m-script using direct mode:
+
+ parallel.importProfile('/apps/all/MATLAB/2015a-EDU/SalomonDirect.settings')
+ cluster = parcluster('SalomonDirect');
+ set(cluster, 'NumWorkers', 48);
+
+ pool = parpool(cluster, 48);
+
+ n=2000;
+
+ W = rand(n,n);
+ W = distributed(W);
+ x = (1:n)';
+ x = distributed(x);
+ spmd
+ [~, name] = system('hostname')
+
+ T = W*x; % Calculation performed on labs, in parallel.
+ % T and W are both codistributed arrays here.
+ end
+ whos % T and W are both distributed arrays here.
+
+ % shut down parallel pool
+ delete(pool)
+
+### Non-interactive Session and Licenses
+
+If you want to run batch jobs with Matlab, be sure to request
+appropriate license features with the PBS Pro scheduler, at least the "
+-l __feature__matlab__MATLAB=1" for EDU variant of Matlab. More
+information about how to check the license features states and how to
+request them with PBS Pro, please [look
+here](../isv_licenses.html).
+
+In case of non-interactive session please read the [following
+information](../isv_licenses.html) on how to modify the
+qsub command to test for available licenses prior getting the resource
+allocation.
+
+### Matlab Distributed Computing Engines start up time
+
+Starting Matlab workers is an expensive process that requires certain
+amount of time. For your information please see the following table:
+
+ |compute nodes|number of workers|start-up time[s]|
+ |---|---|---|
+ |16|384|831|
+ |8|192|807|
+ |4|96|483|
+ |2|48|16|
+
+MATLAB on UV2000Â
+-----------------
+
+UV2000 machine available in queue "qfat" can be used for MATLAB
+computations. This is a SMP NUMA machine with large amount of RAM, which
+can be beneficial for certain types of MATLAB jobs. CPU cores are
+allocated in chunks of 8 for this machine.
+
+You can use MATLAB on UV2000 in two parallel modes :
+
+### Threaded mode
+
+Since this is a SMP machine, you can completely avoid using Parallel
+Toolbox and use only MATLAB's threading. MATLAB will automatically
+detect the number of cores you have allocated and will setÂ
+maxNumCompThreads accordingly and certain
+operations, such as fft, , eig, svd,
+etc. will be automatically run in threads. The advantage of this mode is
+that you don't need to modify your existing sequential codes.
+
+### Local cluster mode
+
+You can also use Parallel Toolbox on UV2000. Use l[ocal cluster
+mode](copy_of_matlab.html#parallel-matlab-batch-job-in-local-mode),
+"SalomonPBSPro" profile will not work.
+
+Â
+
+Â
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/introduction.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/introduction.md
new file mode 100644
index 0000000000000000000000000000000000000000..6c425451b294e75ad697aaca3de1dfe83491ab1a
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/introduction.md
@@ -0,0 +1,48 @@
+Numerical languages
+===================
+
+Interpreted languages for numerical computations and analysis
+
+
+
+Introduction
+------------
+
+This section contains a collection of high-level interpreted languages,
+primarily intended for numerical computations.
+
+Matlab
+------
+
+MATLAB®^ is a high-level language and interactive environment for
+numerical computation, visualization, and programming.
+
+ $ module load MATLAB/2015b-EDU
+ $ matlab
+
+Read more at the [Matlab
+page](matlab.html).
+
+Octave
+------
+
+GNU Octave is a high-level interpreted language, primarily intended for
+numerical computations. The Octave language is quite similar to Matlab
+so that most programs are easily portable.
+
+ $ module load Octave
+ $ octave
+
+Read more at the [Octave page](octave.html).
+
+R
+-
+
+The R is an interpreted language and environment for statistical
+computing and graphics.
+
+ $ module load R
+ $ R
+
+Read more at the [R page](r.html).
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/matlab.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/matlab.md
new file mode 100644
index 0000000000000000000000000000000000000000..9b6b8a062e6c52bfc5a860b3078ece7ea9e14be2
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/matlab.md
@@ -0,0 +1,263 @@
+Matlab 2013-2014
+================
+
+
+
+Introduction
+------------
+
+This document relates to the old versions R2013 and R2014. For MATLAB
+2015, please use [this documentation
+instead](copy_of_matlab.html).
+
+Matlab is available in the latest stable version. There are always two
+variants of the release:
+
+- Non commercial or so called EDU variant, which can be used for
+ common research and educational purposes.
+- Commercial or so called COM variant, which can used also for
+ commercial activities. The licenses for commercial variant are much
+ more expensive, so usually the commercial variant has only subset of
+ features compared to the EDU available.
+
+Â
+
+To load the latest version of Matlab load the module
+
+ $ module load matlab
+
+By default the EDU variant is marked as default. If you need other
+version or variant, load the particular version. To obtain the list of
+available versions use
+
+ $ module avail matlab
+
+If you need to use the Matlab GUI to prepare your Matlab programs, you
+can use Matlab directly on the login nodes. But for all computations use
+Matlab on the compute nodes via PBS Pro scheduler.
+
+If you require the Matlab GUI, please follow the general informations
+about [running graphical
+applications](https://docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/resolveuid/11e53ad0d2fd4c5187537f4baeedff33).
+
+Matlab GUI is quite slow using the X forwarding built in the PBS (qsub
+-X), so using X11 display redirection either via SSH or directly by
+xauth (please see the "GUI Applications on Compute Nodes over VNC" part
+[here](https://docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/resolveuid/11e53ad0d2fd4c5187537f4baeedff33))
+is recommended.
+
+To run Matlab with GUI, use
+
+ $ matlab
+
+To run Matlab in text mode, without the Matlab Desktop GUI environment,
+use
+
+ $ matlab -nodesktop -nosplash
+
+plots, images, etc... will be still available.
+
+Running parallel Matlab using Distributed Computing Toolbox / Engine
+--------------------------------------------------------------------
+
+Recommended parallel mode for running parallel Matlab on Anselm is
+MPIEXEC mode. In this mode user allocates resources through PBS prior to
+starting Matlab. Once resources are granted the main Matlab instance is
+started on the first compute node assigned to job by PBS and workers are
+started on all remaining nodes. User can use both interactive and
+non-interactive PBS sessions. This mode guarantees that the data
+processing is not performed on login nodes, but all processing is on
+compute nodes.
+
+Â 
+
+For the performance reasons Matlab should use system MPI. On Anselm the
+supported MPI implementation for Matlab is Intel MPI. To switch to
+system MPI user has to override default Matlab setting by creating new
+configuration file in its home directory. The path and file name has to
+be exactly the same as in the following listing:
+
+ $ vim ~/matlab/mpiLibConf.m
+
+ function [lib, extras] = mpiLibConf
+ %MATLAB MPI Library overloading for Infiniband Networks
+
+ mpich = '/opt/intel/impi/4.1.1.036/lib64/';
+
+ disp('Using Intel MPI 4.1.1.036 over Infiniband')
+
+ lib = strcat(mpich, 'libmpich.so');
+ mpl = strcat(mpich, 'libmpl.so');
+ opa = strcat(mpich, 'libopa.so');
+
+ extras = {};
+
+System MPI library allows Matlab to communicate through 40Gbps
+Infiniband QDR interconnect instead of slower 1Gb ethernet network.
+
+Please note: The path to MPI library in "mpiLibConf.m" has to match with
+version of loaded Intel MPI module. In this example the version
+4.1.1.036 of Iintel MPI is used by Matlab and therefore module
+impi/4.1.1.036Â has to be loaded prior to starting Matlab.
+
+### Parallel Matlab interactive session
+
+Once this file is in place, user can request resources from PBS.
+Following example shows how to start interactive session with support
+for Matlab GUI. For more information about GUI based applications on
+Anselm see [this
+page](https://docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/resolveuid/11e53ad0d2fd4c5187537f4baeedff33).
+
+ $ xhost +
+ $ qsub -I -v DISPLAY=$(uname -n):$(echo $DISPLAY | cut -d ':' -f 2) -A NONE-0-0 -q qexp -l select=4:ncpus=16:mpiprocs=16 -l walltime=00:30:00
+ -l feature__matlab__MATLAB=1
+
+This qsub command example shows how to run Matlab with 32 workers in
+following configuration: 2 nodes (use all 16 cores per node) and 16
+workers = mpirocs per node (-l select=2:ncpus=16:mpiprocs=16). If user
+requires to run smaller number of workers per node then the "mpiprocs"
+parameter has to be changed.
+
+The second part of the command shows how to request all necessary
+licenses. In this case 1 Matlab-EDU license and 32 Distributed Computing
+Engines licenses.
+
+Once the access to compute nodes is granted by PBS, user can load
+following modules and start Matlab:Â
+
+ cn79$ module load matlab/R2013a-EDU
+ cn79$ module load impi/4.1.1.036
+ cn79$ matlab &
+
+### Parallel Matlab batch job
+
+To run matlab in batch mode, write an matlab script, then write a bash
+jobscript and execute via the qsub command. By default, matlab will
+execute one matlab worker instance per allocated core.
+
+ #!/bin/bash
+ #PBS -A PROJECT ID
+ #PBS -q qprod
+ #PBS -l select=2:ncpus=16:mpiprocs=16:ompthreads=1
+
+ # change to shared scratch directory
+ SCR=/scratch/$USER/$PBS_JOBID
+ mkdir -p $SCR ; cd $SCR || exit
+
+ # copy input file to scratch
+ cp $PBS_O_WORKDIR/matlabcode.m .
+
+ # load modules
+ module load matlab/R2013a-EDU
+ module load impi/4.1.1.036
+
+ # execute the calculation
+ matlab -nodisplay -r matlabcode > output.out
+
+ # copy output file to home
+ cp output.out $PBS_O_WORKDIR/.
+
+This script may be submitted directly to the PBS workload manager via
+the qsub command. The inputs and matlab script are in matlabcode.m
+file, outputs in output.out file. Note the missing .m extension in the
+matlab -r matlabcodefile call, **the .m must not be included**. Note
+that the **shared /scratch must be used**. Further, it is **important to
+include quit** statement at the end of the matlabcode.m script.
+
+Submit the jobscript using qsub
+
+ $ qsub ./jobscript
+
+### Parallel Matlab program example
+
+The last part of the configuration is done directly in the user Matlab
+script before Distributed Computing Toolbox is started.
+
+ sched = findResource('scheduler', 'type', 'mpiexec');
+ set(sched, 'MpiexecFileName', '/apps/intel/impi/4.1.1/bin/mpirun');
+ set(sched, 'EnvironmentSetMethod', 'setenv');
+
+This script creates scheduler object "sched" of type "mpiexec" that
+starts workers using mpirun tool. To use correct version of mpirun, the
+second line specifies the path to correct version of system Intel MPI
+library.
+
+Please note: Every Matlab script that needs to initialize/use matlabpool
+has to contain these three lines prior to calling matlabpool(sched, ...)
+function.Â
+
+The last step is to start matlabpool with "sched" object and correct
+number of workers. In this case qsub asked for total number of 32 cores,
+therefore the number of workers is also set to 32.
+
+ matlabpool(sched,32);
+
+
+ ... parallel code ...
+
+
+ matlabpool close
+
+The complete example showing how to use Distributed Computing Toolbox is
+show here.Â
+
+ sched = findResource('scheduler', 'type', 'mpiexec');
+ set(sched, 'MpiexecFileName', '/apps/intel/impi/4.1.1/bin/mpirun')
+ set(sched, 'EnvironmentSetMethod', 'setenv')
+ set(sched, 'SubmitArguments', '')
+ sched
+
+ matlabpool(sched,32);
+
+ n=2000;
+
+ W = rand(n,n);
+ W = distributed(W);
+ x = (1:n)';
+ x = distributed(x);
+ spmd
+ [~, name] = system('hostname')
+ Â Â Â
+ Â Â Â T = W*x; % Calculation performed on labs, in parallel.
+ Â Â Â Â Â Â Â Â Â Â Â Â % T and W are both codistributed arrays here.
+ end
+ T;
+ whos        % T and W are both distributed arrays here.
+
+ matlabpool close
+ quit
+
+You can copy and paste the example in a .m file and execute. Note that
+the matlabpool size should correspond to **total number of cores**
+available on allocated nodes.
+
+### Non-interactive Session and Licenses
+
+If you want to run batch jobs with Matlab, be sure to request
+appropriate license features with the PBS Pro scheduler, at least the "
+-l __feature__matlab__MATLAB=1" for EDU variant of Matlab. More
+information about how to check the license features states and how to
+request them with PBS Pro, please [look
+here](../isv_licenses.html).
+
+In case of non-interactive session please read the [following
+information](../isv_licenses.html) on how to modify the
+qsub command to test for available licenses prior getting the resource
+allocation.
+
+### Matlab Distributed Computing Engines start up time
+
+Starting Matlab workers is an expensive process that requires certain
+amount of time. For your information please see the following table:
+
+ |compute nodes|number of workers|start-up time[s]|
+ |---|---|---|
+ 16 256 1008
+ 8 128 534
+ 4 64 333
+ 2 32 210
+
+Â
+
+Â
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/octave.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/octave.md
new file mode 100644
index 0000000000000000000000000000000000000000..6db86f6251cf7ff58eda6530eddab0dae8ab4de9
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/octave.md
@@ -0,0 +1,148 @@
+Octave
+======
+
+
+
+Introduction
+------------
+
+GNU Octave is a high-level interpreted language, primarily intended for
+numerical computations. It provides capabilities for the numerical
+solution of linear and nonlinear problems, and for performing other
+numerical experiments. It also provides extensive graphics capabilities
+for data visualization and manipulation. Octave is normally used through
+its interactive command line interface, but it can also be used to write
+non-interactive programs. The Octave language is quite similar to Matlab
+so that most programs are easily portable. Read more on
+<http://www.gnu.org/software/octave/>***
+
+Two versions of octave are available on Anselm, via module
+
+ Version module
+ ----------------------------------------------------- |---|---|-----------------
+ Octave 3.8.2, compiled with GCC and Multithreaded MKL Octave/3.8.2-gimkl-2.11.5
+ Octave 4.0.1, compiled with GCC and Multithreaded MKL Octave/4.0.1-gimkl-2.11.5
+ Octave 4.0.0, compiled with >GCC and OpenBLAS Octave/4.0.0-foss-2015g
+
+Â Modules and execution
+----------------------
+
+ $ module load Octave
+
+The octave on Anselm is linked to highly optimized MKL mathematical
+library. This provides threaded parallelization to many octave kernels,
+notably the linear algebra subroutines. Octave runs these heavy
+calculation kernels without any penalty. By default, octave would
+parallelize to 16 threads. You may control the threads by setting the
+OMP_NUM_THREADS environment variable.
+
+To run octave interactively, log in with ssh -X parameter for X11
+forwarding. Run octave:
+
+ $ octave
+
+To run octave in batch mode, write an octave script, then write a bash
+jobscript and execute via the qsub command. By default, octave will use
+16 threads when running MKL kernels.
+
+ #!/bin/bash
+
+ # change to local scratch directory
+ cd /lscratch/$PBS_JOBID || exit
+
+ # copy input file to scratch
+ cp $PBS_O_WORKDIR/octcode.m .
+
+ # load octave module
+ module load octave
+
+ # execute the calculation
+ octave -q --eval octcode > output.out
+
+ # copy output file to home
+ cp output.out $PBS_O_WORKDIR/.
+
+ #exit
+ exit
+
+This script may be submitted directly to the PBS workload manager via
+the qsub command. The inputs are in octcode.m file, outputs in
+output.out file. See the single node jobscript example in the [Job
+execution
+section](http://support.it4i.cz/docs/anselm-cluster-documentation/resource-allocation-and-job-execution).
+
+The octave c compiler mkoctfile calls the GNU gcc 4.8.1 for compiling
+native c code. This is very useful for running native c subroutines in
+octave environment.
+
+ $ mkoctfile -v
+
+Octave may use MPI for interprocess communication
+This functionality is currently not supported on Anselm cluster. In case
+you require the octave interface to MPI, please contact [Anselm
+support](https://support.it4i.cz/rt/).
+
+Xeon Phi Support
+----------------
+
+Octave may take advantage of the Xeon Phi accelerators. This will only
+work on the [Intel Xeon Phi](../intel-xeon-phi.html)
+[accelerated nodes](../../compute-nodes.html).
+
+### Automatic offload support
+
+Octave can accelerate BLAS type operations (in particular the Matrix
+Matrix multiplications] on the Xeon Phi accelerator, via [Automatic
+Offload using the MKL
+library](../intel-xeon-phi.html#section-3)
+
+Example
+
+ $ export OFFLOAD_REPORT=2
+ $ export MKL_MIC_ENABLE=1
+ $ module load octave
+ $ octave -q
+ octave:1> A=rand(10000); B=rand(10000);
+ octave:2> tic; C=A*B; toc
+ [MKL] [MIC --] [AO Function]Â Â Â DGEMM
+ [MKL] [MIC --] [AO DGEMM Workdivision]Â Â Â 0.32 0.68
+ [MKL] [MIC 00] [AO DGEMM CPU Time]Â Â Â 2.896003 seconds
+ [MKL] [MIC 00] [AO DGEMM MIC Time]Â Â Â 1.967384 seconds
+ [MKL] [MIC 00] [AO DGEMM CPU->MIC Data]Â Â Â 1347200000 bytes
+ [MKL] [MIC 00] [AO DGEMM MIC->CPU Data]Â Â Â 2188800000 bytes
+ Elapsed time is 2.93701 seconds.
+
+In this example, the calculation was automatically divided among the CPU
+cores and the Xeon Phi MIC accelerator, reducing the total runtime from
+6.3 secs down to 2.9 secs.
+
+### Native support
+
+A version of [native](../intel-xeon-phi.html#section-4)
+Octave is compiled for Xeon Phi accelerators. Some limitations apply for
+this version:
+
+- Only command line support. GUI, graph plotting etc. is
+ not supported.
+- Command history in interactive mode is not supported.
+
+Octave is linked with parallel Intel MKL, so it best suited for batch
+processing of tasks that utilize BLAS, LAPACK and FFT operations. By
+default, number of threads is set to 120, you can control this
+with > OMP_NUM_THREADS environment
+variable.
+
+Calculations that do not employ parallelism (either by using parallel
+MKL eg. via matrix operations, fork()
+function, [parallel
+package](http://octave.sourceforge.net/parallel/) or
+other mechanism) will actually run slower than on host CPU.
+
+To use Octave on a node with Xeon Phi:
+
+ $ ssh mic0 # login to the MIC card
+ $ source /apps/tools/octave/3.8.2-mic/bin/octave-env.sh # set up environment variables
+ $ octave -q /apps/tools/octave/3.8.2-mic/example/test0.m # run an exampleÂ
+
+Â
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/r.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/r.md
new file mode 100644
index 0000000000000000000000000000000000000000..694a9d570eb57a6c8a23934110518d13bca2ae08
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-languages/r.md
@@ -0,0 +1,441 @@
+R
+=
+
+
+
+Introduction
+------------
+
+The R is a language and environment for statistical computing and
+graphics. R provides a wide variety of statistical (linear and
+nonlinear modelling, classical statistical tests, time-series analysis,
+classification, clustering, ...) and graphical techniques, and is highly
+extensible.
+
+One of R's strengths is the ease with which well-designed
+publication-quality plots can be produced, including mathematical
+symbols and formulae where needed. Great care has been taken over the
+defaults for the minor design choices in graphics, but the user retains
+full control.
+
+Another convenience is the ease with which the C code or third party
+libraries may be integrated within R.
+
+Extensive support for parallel computing is available within R.
+
+Read more on <http://www.r-project.org/>,
+<http://cran.r-project.org/doc/manuals/r-release/R-lang.html>
+
+Modules
+-------
+
+**The R version 3.0.1 is available on Anselm, along with GUI interface
+Rstudio
+
+ |Application|Version|module|
+ ------- |---|---|---- ---------
+ **R** R 3.0.1 R
+ |**Rstudio**|Rstudio 0.97|Rstudio|
+
+ $ module load R
+
+Execution
+---------
+
+The R on Anselm is linked to highly optimized MKL mathematical
+library. This provides threaded parallelization to many R kernels,
+notably the linear algebra subroutines. The R runs these heavy
+calculation kernels without any penalty. By default, the R would
+parallelize to 16 threads. You may control the threads by setting the
+OMP_NUM_THREADS environment variable.
+
+### Interactive execution
+
+To run R interactively, using Rstudio GUI, log in with ssh -X parameter
+for X11 forwarding. Run rstudio:
+
+ $ module load Rstudio
+ $ rstudio
+
+### Batch execution
+
+To run R in batch mode, write an R script, then write a bash jobscript
+and execute via the qsub command. By default, R will use 16 threads when
+running MKL kernels.
+
+Example jobscript:
+
+ #!/bin/bash
+
+ # change to local scratch directory
+ cd /lscratch/$PBS_JOBID || exit
+
+ # copy input file to scratch
+ cp $PBS_O_WORKDIR/rscript.R .
+
+ # load R module
+ module load R
+
+ # execute the calculation
+ R CMD BATCH rscript.R routput.out
+
+ # copy output file to home
+ cp routput.out $PBS_O_WORKDIR/.
+
+ #exit
+ exit
+
+This script may be submitted directly to the PBS workload manager via
+the qsub command. The inputs are in rscript.R file, outputs in
+routput.out file. See the single node jobscript example in the [Job
+execution
+section](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+
+Parallel R
+----------
+
+Parallel execution of R may be achieved in many ways. One approach is
+the implied parallelization due to linked libraries or specially enabled
+functions, as [described
+above](r.html#interactive-execution). In the following
+sections, we focus on explicit parallelization, where parallel
+constructs are directly stated within the R script.
+
+Package parallel
+--------------------
+
+The package parallel provides support for parallel computation,
+including by forking (taken from package multicore), by sockets (taken
+from package snow) and random-number generation.
+
+The package is activated this way:
+
+ $ R
+ > library(parallel)
+
+More information and examples may be obtained directly by reading the
+documentation available in R
+
+ > ?parallel
+ > library(help = "parallel")
+ > vignette("parallel")
+
+Download the package
+[parallell](package-parallel-vignette) vignette.
+
+The forking is the most simple to use. Forking family of functions
+provide parallelized, drop in replacement for the serial apply() family
+of functions.
+
+Forking via package parallel provides functionality similar to OpenMP
+construct
+#omp parallel for
+
+Only cores of single node can be utilized this way!
+
+Forking example:
+
+ library(parallel)
+
+ #integrand function
+ f <- function(i,h) {
+ x <- h*(i-0.5)
+ return (4/(1 + x*x))
+ }
+
+ #initialize
+ size <- detectCores()
+
+ while (TRUE)
+ {
+ #read number of intervals
+ cat("Enter the number of intervals: (0 quits) ")
+ fp<-file("stdin"); n<-scan(fp,nmax=1); close(fp)
+
+ if(n<=0) break
+
+ #run the calculation
+ n <- max(n,size)
+ h <- 1.0/n
+
+ i <- seq(1,n);
+ pi3 <- h*sum(simplify2array(mclapply(i,f,h,mc.cores=size)));
+
+ #print results
+ cat(sprintf("Value of PI %16.14f, diff= %16.14fn",pi3,pi3-pi))
+ }
+
+The above example is the classic parallel example for calculating the
+number π. Note the **detectCores()** and **mclapply()** functions.
+Execute the example as:
+
+ $ R --slave --no-save --no-restore -f pi3p.R
+
+Every evaluation of the integrad function runs in parallel on different
+process.
+
+Package Rmpi
+------------
+
+package Rmpi provides an interface (wrapper) to MPI APIs.
+
+It also provides interactive R slave environment. On Anselm, Rmpi
+provides interface to the
+[OpenMPI](../mpi-1/Running_OpenMPI.html).
+
+Read more on Rmpi at <http://cran.r-project.org/web/packages/Rmpi/>,
+reference manual is available at
+<http://cran.r-project.org/web/packages/Rmpi/Rmpi.pdf>
+
+When using package Rmpi, both openmpi and R modules must be loaded
+
+ $ module load openmpi
+ $ module load R
+
+Rmpi may be used in three basic ways. The static approach is identical
+to executing any other MPI programm. In addition, there is Rslaves
+dynamic MPI approach and the mpi.apply approach. In the following
+section, we will use the number π integration example, to illustrate all
+these concepts.
+
+### static Rmpi
+
+Static Rmpi programs are executed via mpiexec, as any other MPI
+programs. Number of processes is static - given at the launch time.
+
+Static Rmpi example:
+
+ library(Rmpi)
+
+ #integrand function
+ f <- function(i,h) {
+ x <- h*(i-0.5)
+ return (4/(1 + x*x))
+ }
+
+ #initialize
+ invisible(mpi.comm.dup(0,1))
+ rank <- mpi.comm.rank()
+ size <- mpi.comm.size()
+ n<-0
+
+ while (TRUE)
+ {
+ #read number of intervals
+ if (rank==0) {
+ cat("Enter the number of intervals: (0 quits) ")
+ fp<-file("stdin"); n<-scan(fp,nmax=1); close(fp)
+ }
+
+ #broadcat the intervals
+ n <- mpi.bcast(as.integer(n),type=1)
+
+ if(n<=0) break
+
+ #run the calculation
+ n <- max(n,size)
+ h <- 1.0/n
+
+ i <- seq(rank+1,n,size);
+ mypi <- h*sum(sapply(i,f,h));
+
+ pi3 <- mpi.reduce(mypi)
+
+ #print results
+ if (rank==0) cat(sprintf("Value of PI %16.14f, diff= %16.14fn",pi3,pi3-pi))
+ }
+
+ mpi.quit()
+
+The above is the static MPI example for calculating the number π. Note
+the **library(Rmpi)** and **mpi.comm.dup()** function calls.
+Execute the example as:
+
+ $ mpiexec R --slave --no-save --no-restore -f pi3.R
+
+### dynamic Rmpi
+
+Dynamic Rmpi programs are executed by calling the R directly. openmpi
+module must be still loaded. The R slave processes will be spawned by a
+function call within the Rmpi program.
+
+Dynamic Rmpi example:
+
+ #integrand function
+ f <- function(i,h) {
+ x <- h*(i-0.5)
+ return (4/(1 + x*x))
+ }
+
+ #the worker function
+ workerpi <- function()
+ {
+ #initialize
+ rank <- mpi.comm.rank()
+ size <- mpi.comm.size()
+ n<-0
+
+ while (TRUE)
+ {
+ #read number of intervals
+ if (rank==0) {
+ cat("Enter the number of intervals: (0 quits) ")
+ fp<-file("stdin"); n<-scan(fp,nmax=1); close(fp)
+ }
+
+ #broadcat the intervals
+ n <- mpi.bcast(as.integer(n),type=1)
+
+ if(n<=0) break
+
+ #run the calculation
+ n <- max(n,size)
+ h <- 1.0/n
+
+ i <- seq(rank+1,n,size);
+ mypi <- h*sum(sapply(i,f,h));
+
+ pi3 <- mpi.reduce(mypi)
+
+ #print results
+ if (rank==0) cat(sprintf("Value of PI %16.14f, diff= %16.14fn",pi3,pi3-pi))
+ }
+ }
+
+ #main
+ library(Rmpi)
+
+ cat("Enter the number of slaves: ")
+ fp<-file("stdin"); ns<-scan(fp,nmax=1); close(fp)
+
+ mpi.spawn.Rslaves(nslaves=ns)
+ mpi.bcast.Robj2slave(f)
+ mpi.bcast.Robj2slave(workerpi)
+
+ mpi.bcast.cmd(workerpi())
+ workerpi()
+
+ mpi.quit()
+
+The above example is the dynamic MPI example for calculating the number
+Ď€. Both master and slave processes carry out the calculation. Note the
+mpi.spawn.Rslaves(), mpi.bcast.Robj2slave()** and the
+mpi.bcast.cmd()** function calls.
+Execute the example as:
+
+ $ R --slave --no-save --no-restore -f pi3Rslaves.R
+
+### mpi.apply Rmpi
+
+mpi.apply is a specific way of executing Dynamic Rmpi programs.
+
+mpi.apply() family of functions provide MPI parallelized, drop in
+replacement for the serial apply() family of functions.
+
+Execution is identical to other dynamic Rmpi programs.
+
+mpi.apply Rmpi example:
+
+ #integrand function
+ f <- function(i,h) {
+ x <- h*(i-0.5)
+ return (4/(1 + x*x))
+ }
+
+ #the worker function
+ workerpi <- function(rank,size,n)
+ {
+ #run the calculation
+ n <- max(n,size)
+ h <- 1.0/n
+
+ i <- seq(rank,n,size);
+ mypi <- h*sum(sapply(i,f,h));
+
+ return(mypi)
+ }
+
+ #main
+ library(Rmpi)
+
+ cat("Enter the number of slaves: ")
+ fp<-file("stdin"); ns<-scan(fp,nmax=1); close(fp)
+
+ mpi.spawn.Rslaves(nslaves=ns)
+ mpi.bcast.Robj2slave(f)
+ mpi.bcast.Robj2slave(workerpi)
+
+ while (TRUE)
+ {
+ #read number of intervals
+ cat("Enter the number of intervals: (0 quits) ")
+ fp<-file("stdin"); n<-scan(fp,nmax=1); close(fp)
+ if(n<=0) break
+
+ #run workerpi
+ i=seq(1,2*ns)
+ pi3=sum(mpi.parSapply(i,workerpi,2*ns,n))
+
+ #print results
+ cat(sprintf("Value of PI %16.14f, diff= %16.14fn",pi3,pi3-pi))
+ }
+
+ mpi.quit()
+
+The above is the mpi.apply MPI example for calculating the number π.
+Only the slave processes carry out the calculation. Note the
+mpi.parSapply(), ** function call. The package
+parallel
+[example](r.html#package-parallel)[above](r.html#package-parallel){.anchor
+may be trivially adapted (for much better performance) to this structure
+using the mclapply() in place of mpi.parSapply().
+
+Execute the example as:
+
+ $ R --slave --no-save --no-restore -f pi3parSapply.R
+
+Combining parallel and Rmpi
+---------------------------
+
+Currently, the two packages can not be combined for hybrid calculations.
+
+Parallel execution
+------------------
+
+The R parallel jobs are executed via the PBS queue system exactly as any
+other parallel jobs. User must create an appropriate jobscript and
+submit via the **qsub**
+
+Example jobscript for [static Rmpi](r.html#static-rmpi)
+parallel R execution, running 1 process per core:
+
+ #!/bin/bash
+ #PBS -q qprod
+ #PBS -N Rjob
+ #PBS -l select=100:ncpus=16:mpiprocs=16:ompthreads=1
+
+ # change to scratch directory
+ SCRDIR=/scratch/$USER/myjob
+ cd $SCRDIR || exit
+
+ # copy input file to scratch
+ cp $PBS_O_WORKDIR/rscript.R .
+
+ # load R and openmpi module
+ module load R
+ module load openmpi
+
+ # execute the calculation
+ mpiexec -bycore -bind-to-core R --slave --no-save --no-restore -f rscript.R
+
+ # copy output file to home
+ cp routput.out $PBS_O_WORKDIR/.
+
+ #exit
+ exit
+
+For more information about jobscripts and MPI execution refer to the
+[Job
+submission](../../resource-allocation-and-job-execution/job-submission-and-execution.html)
+and general [MPI](../mpi-1.html) sections.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/fftw.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/fftw.md
new file mode 100644
index 0000000000000000000000000000000000000000..dc843fe8be9b69939bcbdbb202714a220d4cfdfd
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/fftw.md
@@ -0,0 +1,91 @@
+FFTW
+====
+
+The discrete Fourier transform in one or more dimensions, MPI parallel
+
+
+
+Â
+
+FFTW is a C subroutine library for computing the discrete Fourier
+transform in one or more dimensions, of arbitrary input size, and of
+both real and complex data (as well as of even/odd data, i.e. the
+discrete cosine/sine transforms or DCT/DST). The FFTW library allows for
+MPI parallel, in-place discrete Fourier transform, with data distributed
+over number of nodes.
+
+Two versions, **3.3.3** and **2.1.5** of FFTW are available on Anselm,
+each compiled for **Intel MPI** and **OpenMPI** using **intel** and
+gnu** compilers. These are available via modules:
+
+<col width="25%" />
+<col width="25%" />
+<col width="25%" />
+<col width="25%" />
+ |Version |Parallelization |module |linker options |
+ | --- | --- |
+ |FFTW3 gcc3.3.3 |pthread, OpenMP |fftw3/3.3.3-gcc |-lfftw3, -lfftw3_threads-lfftw3_omp |
+ |FFTW3 icc3.3.3\ |pthread, OpenMP |fftw3 |-lfftw3, -lfftw3_threads-lfftw3_omp |
+ |FFTW2 gcc2.1.5\ |pthread |fftw2/2.1.5-gcc |-lfftw, -lfftw_threads |
+ |FFTW2 icc2.1.5 |pthread |fftw2 |-lfftw, -lfftw_threads |
+ |FFTW3 gcc3.3.3 |OpenMPI |fftw-mpi3/3.3.3-gcc |-lfftw3_mpi |
+ |FFTW3 icc3.3.3 |Intel MPI |fftw3-mpi |-lfftw3_mpi |
+ |FFTW2 gcc2.1.5 |OpenMPI |fftw2-mpi/2.1.5-gcc |-lfftw_mpi |
+ |FFTW2 gcc2.1.5 |IntelMPI |fftw2-mpi/2.1.5-gcc |-lfftw_mpi |
+
+ $ module load fftw3
+
+The module sets up environment variables, required for linking and
+running fftw enabled applications. Make sure that the choice of fftw
+module is consistent with your choice of MPI library. Mixing MPI of
+different implementations may have unpredictable results.
+
+Example
+-------
+
+ #include <fftw3-mpi.h>
+ int main(int argc, char **argv)
+ {
+ Â Â Â const ptrdiff_t N0 = 100, N1 = 1000;
+ Â Â Â fftw_plan plan;
+ Â Â Â fftw_complex *data;
+ Â Â Â ptrdiff_t alloc_local, local_n0, local_0_start, i, j;
+
+ Â Â Â MPI_Init(&argc, &argv);
+ Â Â Â fftw_mpi_init();
+
+ Â Â Â /* get local data size and allocate */
+ Â Â Â alloc_local = fftw_mpi_local_size_2d(N0, N1, MPI_COMM_WORLD,
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â &local_n0, &local_0_start);
+ Â Â Â data = fftw_alloc_complex(alloc_local);
+
+ Â Â Â /* create plan for in-place forward DFT */
+ Â Â Â plan = fftw_mpi_plan_dft_2d(N0, N1, data, data, MPI_COMM_WORLD,
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â FFTW_FORWARD, FFTW_ESTIMATE);
+
+ Â Â Â /* initialize data */
+ Â Â Â for (i = 0; i < local_n0; ++i) for (j = 0; j < N1; ++j)
+ Â Â Â {Â Â data[i*N1 + j][0] = i;
+ Â Â Â Â Â Â Â data[i*N1 + j][1] = j; }
+
+ Â Â Â /* compute transforms, in-place, as many times as desired */
+ Â Â Â fftw_execute(plan);
+
+ Â Â Â fftw_destroy_plan(plan);
+
+ Â Â Â MPI_Finalize();
+ }
+
+Load modules and compile:
+
+ $ module load impi intel
+ $ module load fftw3-mpi
+
+ $ mpicc testfftw3mpi.c -o testfftw3mpi.x -Wl,-rpath=$LIBRARY_PATH -lfftw3_mpi
+
+ Run the example as [Intel MPI
+program](../mpi-1/running-mpich2.html).
+
+Read more on FFTW usage on the [FFTW
+website.](http://www.fftw.org/fftw3_doc/)
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/gsl.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/gsl.md
new file mode 100644
index 0000000000000000000000000000000000000000..35894dad44cd6d9d3990a456db65894d75c7961e
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/gsl.md
@@ -0,0 +1,164 @@
+GSL
+===
+
+The GNU Scientific Library. Provides a wide range of mathematical
+routines.
+
+
+
+Introduction
+------------
+
+The GNU Scientific Library (GSL) provides a wide range of mathematical
+routines such as random number generators, special functions and
+least-squares fitting. There are over 1000 functions in total. The
+routines have been written from scratch in C, and present a modern
+Applications Programming Interface (API) for C programmers, allowing
+wrappers to be written for very high level languages.
+
+The library covers a wide range of topics in numerical computing.
+Routines are available for the following areas:
+
+ ------------------ |---|---|-------------- ------------------------
+ Complex Numbers Roots of Polynomials
+
+ Special Functions Vectors and Matrices
+
+ Permutations Combinations
+
+ Sorting BLAS Support
+
+ Linear Algebra CBLAS Library
+
+ Fast Fourier Transforms Eigensystems
+
+ Random Numbers Quadrature
+
+ Random Distributions Quasi-Random Sequences
+
+ Histograms Statistics
+
+ Monte Carlo Integration N-Tuples
+
+ Differential Equations Simulated Annealing
+
+ Numerical Interpolation
+ Differentiation
+
+ Series Acceleration Chebyshev Approximations
+
+ Root-Finding Discrete Hankel
+ Transforms
+
+ Least-Squares Fitting Minimization
+
+ IEEE Floating-Point Physical Constants
+
+ Basis Splines Wavelets
+ ------------------ |---|---|-------------- ------------------------
+
+Modules
+-------
+
+The GSL 1.16 is available on Anselm, compiled for GNU and Intel
+compiler. These variants are available via modules:
+
+ Module Compiler
+ ----------------- |---|---|-
+ gsl/1.16-gcc gcc 4.8.6
+ gsl/1.16-icc(default) icc
+
+ Â $ module load gsl
+
+The module sets up environment variables, required for linking and
+running GSL enabled applications. This particular command loads the
+default module, which is gsl/1.16-icc
+
+Linking
+-------
+
+Load an appropriate gsl module. Link using **-lgsl** switch to link your
+code against GSL. The GSL depends on cblas API to BLAS library, which
+must be supplied for linking. The BLAS may be provided, for example from
+the MKL library, as well as from the BLAS GSL library (-lgslcblas).
+Using the MKL is recommended.
+
+### Compiling and linking with Intel compilers
+
+ $ module load intel
+ $ module load gsl
+ $ icc myprog.c -o myprog.x -Wl,-rpath=$LIBRARY_PATH -mkl -lgsl
+
+### Compiling and linking with GNU compilers
+
+ $ module load gcc
+ $ module load mkl
+ $ module load gsl/1.16-gcc
+ $ gcc myprog.c -o myprog.x -Wl,-rpath=$LIBRARY_PATH -lmkl_intel_lp64 -lmkl_gnu_thread -lmkl_core -lgomp -lgsl
+
+Example
+-------
+
+Following is an example of discrete wavelet transform implemented by
+GSL:
+
+ #include <stdio.h>
+ #include <math.h>
+ #include <gsl/gsl_sort.h>
+ #include <gsl/gsl_wavelet.h>
+
+ int
+ main (int argc, char **argv)
+ {
+ Â int i, n = 256, nc = 20;
+ Â double *data = malloc (n * sizeof (double));
+ Â double *abscoeff = malloc (n * sizeof (double));
+ Â size_t *p = malloc (n * sizeof (size_t));
+
+ Â gsl_wavelet *w;
+ Â gsl_wavelet_workspace *work;
+
+ Â w = gsl_wavelet_alloc (gsl_wavelet_daubechies, 4);
+ Â work = gsl_wavelet_workspace_alloc (n);
+
+ Â for (i=0; i<n; i++)
+ Â data[i] = sin (3.141592654*(double)i/256.0);
+
+ Â gsl_wavelet_transform_forward (w, data, 1, n, work);
+
+ Â for (i = 0; i < n; i++)
+ Â Â Â {
+ Â Â Â Â Â abscoeff[i] = fabs (data[i]);
+ Â Â Â }
+ Â
+ Â gsl_sort_index (p, abscoeff, 1, n);
+ Â
+ Â for (i = 0; (i + nc) < n; i++)
+ Â Â Â data[p[i]] = 0;
+ Â
+ Â gsl_wavelet_transform_inverse (w, data, 1, n, work);
+ Â
+ Â for (i = 0; i < n; i++)
+ Â Â Â {
+ Â Â Â Â Â printf ("%gn", data[i]);
+ Â Â Â }
+ Â
+ Â gsl_wavelet_free (w);
+ Â gsl_wavelet_workspace_free (work);
+
+ Â free (data);
+ Â free (abscoeff);
+ Â free (p);
+ Â return 0;
+ }
+
+Load modules and compile:
+
+ $ module load intel gsl
+ icc dwt.c -o dwt.x -Wl,-rpath=$LIBRARY_PATH -mkl -lgsl
+
+In this example, we compile the dwt.c code using the Intel compiler and
+link it to the MKL and GSL library, note the -mkl and -lgsl options. The
+library search path is compiled in, so that no modules are necessary to
+run the code.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/hdf5.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/hdf5.md
new file mode 100644
index 0000000000000000000000000000000000000000..7c6d9def6a429dcfb1695f4872af6cab1c8bc091
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/hdf5.md
@@ -0,0 +1,120 @@
+HDF5
+====
+
+Hierarchical Data Format library. Serial and MPI parallel version.
+
+Â
+
+[HDF5 (Hierarchical Data Format)](http://www.hdfgroup.org/HDF5/) is a
+general purpose library and file format for storing scientific data.
+HDF5 can store two primary objects: datasets and groups. A dataset is
+essentially a multidimensional array of data elements, and a group is a
+structure for organizing objects in an HDF5 file. Using these two basic
+objects, one can create and store almost any kind of scientific data
+structure, such as images, arrays of vectors, and structured and
+unstructured grids. You can also mix and match them in HDF5 files
+according to your needs.
+
+Versions **1.8.11** and **1.8.13** of HDF5 library are available on
+Anselm, compiled for **Intel MPI** and **OpenMPI** using **intel** and
+gnu** compilers. These are available via modules:
+
+ |Version |Parallelization |module |C linker options<th align="left">C++ linker options<th align="left">Fortran linker options |
+ | --- | --- |
+ |HDF5 icc serial |pthread |hdf5/1.8.11 |$HDF5_INC $HDF5_SHLIB |$HDF5_INC $HDF5_CPP_LIB |$HDF5_INC $HDF5_F90_LIB |
+ |HDF5 icc parallel MPI\ |pthread, IntelMPI |hdf5-parallel/1.8.11 |$HDF5_INC $HDF5_SHLIB |Not supported |$HDF5_INC $HDF5_F90_LIB |
+ |HDF5 icc serial |pthread |hdf5/1.8.13 |$HDF5_INC $HDF5_SHLIB |$HDF5_INC $HDF5_CPP_LIB |$HDF5_INC $HDF5_F90_LIB |
+ |HDF5 icc parallel MPI\ |pthread, IntelMPI |hdf5-parallel/1.8.13 |$HDF5_INC $HDF5_SHLIB |Not supported |$HDF5_INC $HDF5_F90_LIB |
+ |HDF5 gcc parallel MPI\ |pthread, OpenMPI 1.6.5, gcc 4.8.1 |hdf5-parallel/1.8.11-gcc |$HDF5_INC $HDF5_SHLIB |Not supported |$HDF5_INC $HDF5_F90_LIB |
+ |HDF5 gcc parallel MPI\ |pthread, OpenMPI 1.6.5, gcc 4.8.1 |hdf5-parallel/1.8.13-gcc |$HDF5_INC $HDF5_SHLIB |Not supported |$HDF5_INC $HDF5_F90_LIB |
+ |HDF5 gcc parallel MPI\ |pthread, OpenMPI 1.8.1, gcc 4.9.0 |hdf5-parallel/1.8.13-gcc49 |$HDF5_INC $HDF5_SHLIB |Not supported |$HDF5_INC $HDF5_F90_LIB |
+
+Â
+
+ $ module load hdf5-parallel
+
+The module sets up environment variables, required for linking and
+running HDF5 enabled applications. Make sure that the choice of HDF5
+module is consistent with your choice of MPI library. Mixing MPI of
+different implementations may have unpredictable results.
+
+Be aware, that GCC version of **HDF5 1.8.11** has serious performance
+issues, since it's compiled with -O0 optimization flag. This version is
+provided only for testing of code compiled only by GCC and IS NOT
+recommended for production computations. For more informations, please
+see:
+<http://www.hdfgroup.org/ftp/HDF5/prev-releases/ReleaseFiles/release5-1811>
+All GCC versions of **HDF5 1.8.13** are not affected by the bug, are
+compiled with -O3 optimizations and are recommended for production
+computations.
+
+Example
+-------
+
+ #include "hdf5.h"
+ #define FILE "dset.h5"
+
+ int main() {
+
+ hid_t file_id, dataset_id, dataspace_id; /* identifiers */
+ hsize_t dims[2];
+ herr_t status;
+ int i, j, dset_data[4][6];
+
+ /* Create a new file using default properties. */
+ file_id = H5Fcreate(FILE, H5F_ACC_TRUNC, H5P_DEFAULT, H5P_DEFAULT);
+
+ /* Create the data space for the dataset. */
+ dims[0] = 4;
+ dims[1] = 6;
+ dataspace_id = H5Screate_simple(2, dims, NULL);
+
+ /* Initialize the dataset. */
+ for (i = 0; i < 4; i++)
+ for (j = 0; j < 6; j++)
+ dset_data[i][j] = i * 6 + j + 1;
+
+ /* Create the dataset. */
+ dataset_id = H5Dcreate2(file_id, "/dset", H5T_STD_I32BE, dataspace_id,
+ H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT);
+
+ /* Write the dataset. */
+ status = H5Dwrite(dataset_id, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT,
+ dset_data);
+
+ status = H5Dread(dataset_id, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT,
+ dset_data);
+
+ /* End access to the dataset and release resources used by it. */
+ status = H5Dclose(dataset_id);
+
+ /* Terminate access to the data space. */
+ status = H5Sclose(dataspace_id);
+
+ /* Close the file. */
+ status = H5Fclose(file_id);
+ }
+
+Load modules and compile:
+
+ $ module load intel impi
+ $ module load hdf5-parallel
+
+ $ mpicc hdf5test.c -o hdf5test.x -Wl,-rpath=$LIBRARY_PATH $HDF5_INC $HDF5_SHLIB
+
+ Run the example as [Intel MPI
+program](../anselm-cluster-documentation/software/mpi-1/running-mpich2.html).
+
+For further informations, please see the website:
+<http://www.hdfgroup.org/HDF5/>
+
+Â
+
+Â
+
+Â
+
+class="smarterwiki-popup-bubble-tip">
+
+btnI=I'm+Feeling+Lucky&btnI=I'm+Feeling+Lucky&q=HDF5%20icc%20serial%09pthread%09hdf5%2F1.8.13%09%24HDF5_INC%20%24HDF5_SHLIB%09%24HDF5_INC%20%24HDF5_CPP_LIB%09%24HDF5_INC%20%24HDF5_F90_LIB%0A%0AHDF5%20icc%20parallel%20MPI%0A%09pthread%2C%20IntelMPI%09hdf5-parallel%2F1.8.13%09%24HDF5_INC%20%24HDF5_SHLIB%09Not%20supported%09%24HDF5_INC%20%24HDF5_F90_LIB+wikipedia "Search Wikipedia"){.smarterwiki-popup-bubble
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/intel-numerical-libraries.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/intel-numerical-libraries.md
new file mode 100644
index 0000000000000000000000000000000000000000..eb98c60fa8913a2ed75576197daf7dfbbe68d988
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/intel-numerical-libraries.md
@@ -0,0 +1,54 @@
+Intel numerical libraries
+=========================
+
+Intel libraries for high performance in numerical computing
+
+
+
+Intel Math Kernel Library
+-------------------------
+
+Intel Math Kernel Library (Intel MKL) is a library of math kernel
+subroutines, extensively threaded and optimized for maximum performance.
+Intel MKL unites and provides these basic components: BLAS, LAPACK,
+ScaLapack, PARDISO, FFT, VML, VSL, Data fitting, Feast Eigensolver and
+many more.
+
+ $ module load mkl
+
+Read more at the [Intel
+MKL](../intel-suite/intel-mkl.html) page.
+
+Intel Integrated Performance Primitives
+---------------------------------------
+
+Intel Integrated Performance Primitives, version 7.1.1, compiled for AVX
+is available, via module ipp. The IPP is a library of highly optimized
+algorithmic building blocks for media and data applications. This
+includes signal, image and frame processing algorithms, such as FFT,
+FIR, Convolution, Optical Flow, Hough transform, Sum, MinMax and many
+more.
+
+ $ module load ipp
+
+Read more at the [Intel
+IPP](../intel-suite/intel-integrated-performance-primitives.html)
+page.
+
+Intel Threading Building Blocks
+-------------------------------
+
+Intel Threading Building Blocks (Intel TBB) is a library that supports
+scalable parallel programming using standard ISO C++ code. It does not
+require special languages or compilers. It is designed to promote
+scalable data parallel programming. Additionally, it fully supports
+nested parallelism, so you can build larger parallel components from
+smaller parallel components. To use the library, you specify tasks, not
+threads, and let the library map tasks onto threads in an efficient
+manner.
+
+ $ module load tbb
+
+Read more at the [Intel
+TBB](../intel-suite/intel-tbb.html) page.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/magma-for-intel-xeon-phi.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/magma-for-intel-xeon-phi.md
new file mode 100644
index 0000000000000000000000000000000000000000..94aae9e9cdec1250d4392676ea5f40b0f6c767bc
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/magma-for-intel-xeon-phi.md
@@ -0,0 +1,93 @@
+MAGMA for Intel Xeon Phi
+========================
+
+Next generation dense algebra library for heterogeneous systems with
+accelerators
+
+### Compiling and linking with MAGMA
+
+To be able to compile and link code with MAGMA library user has to load
+following module:
+
+ $ module load magma/1.3.0-mic
+
+To make compilation more user friendly module also sets these two
+environment variables:
+
+MAGMA_INC - contains paths to the MAGMA header files (to be used for
+compilation step)
+
+MAGMA_LIBS - contains paths to MAGMA libraries (to be used for linking
+step). Â
+
+Compilation example:
+
+ $ icc -mkl -O3 -DHAVE_MIC -DADD_ -Wall $MAGMA_INC -c testing_dgetrf_mic.cpp -o testing_dgetrf_mic.o
+
+ $ icc -mkl -O3 -DHAVE_MIC -DADD_ -Wall -fPIC -Xlinker -zmuldefs -Wall -DNOCHANGE -DHOST testing_dgetrf_mic.o -o testing_dgetrf_mic $MAGMA_LIBS
+
+Â
+
+### Running MAGMA code
+
+MAGMA implementation for Intel MIC requires a MAGMA server running on
+accelerator prior to executing the user application. The server can be
+started and stopped using following scripts:
+
+To start MAGMA server use:
+$MAGMAROOT/start_magma_server**
+
+To stop the server use:
+$MAGMAROOT/stop_magma_server**
+
+For deeper understanding how the MAGMA server is started, see the
+following script:
+$MAGMAROOT/launch_anselm_from_mic.sh**
+
+To test if the MAGMA server runs properly we can run one of examples
+that are part of the MAGMA installation:
+
+ [user@cn204 ~]$ $MAGMAROOT/testing/testing_dgetrf_mic
+
+ [user@cn204 ~]$ export OMP_NUM_THREADS=16
+
+ [lriha@cn204 ~]$ $MAGMAROOT/testing/testing_dgetrf_mic
+ Usage: /apps/libs/magma-mic/magmamic-1.3.0/testing/testing_dgetrf_mic [options] [-h|--help]
+
+ Â MÂ Â Â Â NÂ Â Â Â CPU GFlop/s (sec)Â Â MAGMA GFlop/s (sec)Â Â ||PA-LU||/(||A||*N)
+ =========================================================================
+ Â 1088Â 1088Â Â Â Â ---Â Â (Â ---Â )Â Â Â Â 13.93 (Â Â 0.06)Â Â Â Â ---
+ Â 2112Â 2112Â Â Â Â ---Â Â (Â ---Â )Â Â Â Â 77.85 (Â Â 0.08)Â Â Â Â ---
+ Â 3136Â 3136Â Â Â Â ---Â Â (Â ---Â )Â Â Â 183.21 (Â Â 0.11)Â Â Â Â ---
+ Â 4160Â 4160Â Â Â Â ---Â Â (Â ---Â )Â Â Â 227.52 (Â Â 0.21)Â Â Â Â ---
+ Â 5184Â 5184Â Â Â Â ---Â Â (Â ---Â )Â Â Â 258.61 (Â Â 0.36)Â Â Â Â ---
+ Â 6208Â 6208Â Â Â Â ---Â Â (Â ---Â )Â Â Â 333.12 (Â Â 0.48)Â Â Â Â ---
+ Â 7232Â 7232Â Â Â Â ---Â Â (Â ---Â )Â Â Â 416.52 (Â Â 0.61)Â Â Â Â ---
+ Â 8256Â 8256Â Â Â Â ---Â Â (Â ---Â )Â Â Â 446.97 (Â Â 0.84)Â Â Â Â ---
+ Â 9280Â 9280Â Â Â Â ---Â Â (Â ---Â )Â Â Â 461.15 (Â Â 1.16)Â Â Â Â ---
+ 10304 10304Â Â Â Â ---Â Â (Â ---Â )Â Â Â 500.70 (Â Â 1.46)Â Â Â Â ---
+
+Â
+
+Please note: MAGMA contains several benchmarks and examples that can be
+found in:
+$MAGMAROOT/testing/**
+
+MAGMA relies on the performance of all CPU cores as well as on the
+performance of the accelerator. Therefore on Anselm number of CPU OpenMP
+threads has to be set to 16: Â **
+export OMP_NUM_THREADS=16**
+
+Â
+
+See more details at [MAGMA home
+page](http://icl.cs.utk.edu/magma/).
+
+References
+----------
+
+[1] MAGMA MIC: Linear Algebra Library for Intel Xeon Phi Coprocessors,
+Jack Dongarra et. al,Â
+[http://icl.utk.edu/projectsfiles/magma/pubs/24-MAGMA_MIC_03.pdf
+](http://icl.utk.edu/projectsfiles/magma/pubs/24-MAGMA_MIC_03.pdf)
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/petsc.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/petsc.md
new file mode 100644
index 0000000000000000000000000000000000000000..5bf88ae2c57af507465e8de23e1a3b25c1253966
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/petsc.md
@@ -0,0 +1,106 @@
+PETSc
+=====
+
+PETSc is a suite of building blocks for the scalable solution of
+scientific and engineering applications modelled by partial differential
+equations. It supports MPI, shared memory, and GPUs through CUDA or
+OpenCL, as well as hybrid MPI-shared memory or MPI-GPU parallelism.
+
+
+
+Introduction
+------------
+
+PETSc (Portable, Extensible Toolkit for Scientific Computation) is a
+suite of building blocks (data structures and routines) for the scalable
+solution of scientific and engineering applications modelled by partial
+differential equations. It allows thinking in terms of high-level
+objects (matrices) instead of low-level objects (raw arrays). Written in
+C language but can also be called from FORTRAN, C++, Python and Java
+codes. It supports MPI, shared memory, and GPUs through CUDA or OpenCL,
+as well as hybrid MPI-shared memory or MPI-GPU parallelism.
+
+Resources
+---------
+
+- [project webpage](http://www.mcs.anl.gov/petsc/)
+- [documentation](http://www.mcs.anl.gov/petsc/documentation/)
+ - [PETSc Users
+ Manual (PDF)](http://www.mcs.anl.gov/petsc/petsc-current/docs/manual.pdf)
+ - [index of all manual
+ pages](http://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/singleindex.html)
+- PRACE Video Tutorial [part
+ 1](http://www.youtube.com/watch?v=asVaFg1NDqY), [part
+ 2](http://www.youtube.com/watch?v=ubp_cSibb9I), [part
+ 3](http://www.youtube.com/watch?v=vJAAAQv-aaw), [part
+ 4](http://www.youtube.com/watch?v=BKVlqWNh8jY), [part
+ 5](http://www.youtube.com/watch?v=iXkbLEBFjlM)
+
+Modules
+-------
+
+You can start using PETSc on Anselm by loading the PETSc module. Module
+names obey this pattern:
+
+ # module load petsc/version-compiler-mpi-blas-variant, e.g.
+ module load petsc/3.4.4-icc-impi-mkl-opt
+
+where `variant` is replaced by one of
+`{dbg, opt, threads-dbg, threads-opt}`. The `opt` variant is compiled
+without debugging information (no `-g` option) and with aggressive
+compiler optimizations (`-O3 -xAVX`). This variant is suitable for
+performance measurements and production runs. In all other cases use the
+debug (`dbg`) variant, because it contains debugging information,
+performs validations and self-checks, and provides a clear stack trace
+and message in case of an error. The other two variants `threads-dbg`
+and `threads-opt` are `dbg` and `opt`, respectively, built with [OpenMP
+and pthreads threading
+support](http://www.mcs.anl.gov/petsc/features/threads.html).
+
+External libraries
+------------------
+
+PETSc needs at least MPI, BLAS and LAPACK. These dependencies are
+currently satisfied with Intel MPI and Intel MKL in Anselm `petsc`
+modules.
+
+PETSc can be linked with a plethora of [external numerical
+libraries](http://www.mcs.anl.gov/petsc/miscellaneous/external.html),
+extending PETSc functionality, e.g. direct linear system solvers,
+preconditioners or partitioners. See below a list of libraries currently
+included in Anselm `petsc` modules.
+
+All these libraries can be used also alone, without PETSc. Their static
+or shared program libraries are available in
+`$PETSC_DIR/$PETSC_ARCH/lib` and header files in
+`$PETSC_DIR/$PETSC_ARCH/include`. `PETSC_DIR` and `PETSC_ARCH` are
+environment variables pointing to a specific PETSc instance based on the
+petsc module loaded.
+
+### Libraries linked to PETSc on Anselm (as of 11 April 2015)
+
+- dense linear algebra
+ - [Elemental](http://libelemental.org/)
+- sparse linear system solvers
+ - [Intel MKL
+ Pardiso](https://software.intel.com/en-us/node/470282)
+ - [MUMPS](http://mumps.enseeiht.fr/)
+ - [PaStiX](http://pastix.gforge.inria.fr/)
+ - [SuiteSparse](http://faculty.cse.tamu.edu/davis/suitesparse.html)
+ - [SuperLU](http://crd.lbl.gov/~xiaoye/SuperLU/#superlu)
+ - [SuperLU_Dist](http://crd.lbl.gov/~xiaoye/SuperLU/#superlu_dist)
+- input/output
+ - [ExodusII](http://sourceforge.net/projects/exodusii/)
+ - [HDF5](http://www.hdfgroup.org/HDF5/)
+ - [NetCDF](http://www.unidata.ucar.edu/software/netcdf/)
+- partitioning
+ - [Chaco](http://www.cs.sandia.gov/CRF/chac.html)
+ - [METIS](http://glaros.dtc.umn.edu/gkhome/metis/metis/overview)
+ - [ParMETIS](http://glaros.dtc.umn.edu/gkhome/metis/parmetis/overview)
+ - [PT-Scotch](http://www.labri.fr/perso/pelegrin/scotch/)
+- preconditioners & multigrid
+ - [Hypre](http://acts.nersc.gov/hypre/)
+ - [Trilinos ML](http://trilinos.sandia.gov/packages/ml/)
+ - [SPAI - Sparse Approximate
+ Inverse](https://bitbucket.org/petsc/pkg-spai)
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/trilinos.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/trilinos.md
new file mode 100644
index 0000000000000000000000000000000000000000..ddd041eeb6ecad4e54a7d009a55fb64a29d7dc78
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/numerical-libraries/trilinos.md
@@ -0,0 +1,74 @@
+Trilinos
+========
+
+Packages for large scale scientific and engineering problems. Provides
+MPI and hybrid parallelization.
+
+### Introduction
+
+Trilinos is a collection of software packages for the numerical solution
+of large scale scientific and engineering problems. It is based on C++
+and feautures modern object-oriented design. Both serial as well as
+parallel computations based on MPI and hybrid parallelization are
+supported within Trilinos packages.
+
+### Installed packages
+
+Current Trilinos installation on ANSELM contains (among others) the
+following main packages
+
+- **Epetra** - core linear algebra package containing classes for
+ manipulation with serial and distributed vectors, matrices,
+ and graphs. Dense linear solvers are supported via interface to BLAS
+ and LAPACK (Intel MKL on ANSELM). Its extension **EpetraExt**
+ contains e.g. methods for matrix-matrix multiplication.
+- **Tpetra** - next-generation linear algebra package. Supports 64bit
+ indexing and arbitrary data type using C++ templates.
+- **Belos** - library of various iterative solvers (CG, block CG,
+ GMRES, block GMRES etc.).
+- **Amesos** - interface to direct sparse solvers.
+- **Anasazi** - framework for large-scale eigenvalue algorithms.
+- **IFPACK** - distributed algebraic preconditioner (includes e.g.
+ incomplete LU factorization)
+- **Teuchos** - common tools packages. This package contains classes
+ for memory management, output, performance monitoring, BLAS and
+ LAPACK wrappers etc.
+
+For the full list of Trilinos packages, descriptions of their
+capabilities, and user manuals see
+[http://trilinos.sandia.gov.](http://trilinos.sandia.gov)
+
+### Installed version
+
+Currently, Trilinos in version 11.2.3 compiled with Intel Compiler is
+installed on ANSELM.
+
+### Compilling against Trilinos
+
+First, load the appropriate module:
+
+ $ module load trilinos
+
+For the compilation of CMake-aware project, Trilinos provides the
+FIND_PACKAGE( Trilinos ) capability, which makes it easy to build
+against Trilinos, including linking against the correct list of
+libraries. For details, see
+<http://trilinos.sandia.gov/Finding_Trilinos.txt>
+
+For compiling using simple makefiles, Trilinos provides Makefile.export
+system, which allows users to include important Trilinos variables
+directly into their makefiles. This can be done simply by inserting the
+following line into the makefile:
+
+ include Makefile.export.Trilinos
+
+or
+
+ include Makefile.export.<package>
+
+if you are interested only in a specific Trilinos package. This will
+give you access to the variables such as Trilinos_CXX_COMPILER,
+Trilinos_INCLUDE_DIRS, Trilinos_LIBRARY_DIRS etc. For the detailed
+description and example makefile see
+<http://trilinos.sandia.gov/Export_Makefile.txt>.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/nvidia-cuda.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/nvidia-cuda.md
new file mode 100644
index 0000000000000000000000000000000000000000..01168124d53b6b2006bb10669c056b33eb97b2c5
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/nvidia-cuda.md
@@ -0,0 +1,312 @@
+nVidia CUDA
+===========
+
+A guide to nVidia CUDA programming and GPU usage
+
+
+
+CUDA Programming on Anselm
+--------------------------
+
+The default programming model for GPU accelerators on Anselm is Nvidia
+CUDA. To set up the environment for CUDA use
+
+ $ module load cuda
+
+If the user code is hybrid and uses both CUDA and MPI, the MPI
+environment has to be set up as well. One way to do this is to use
+the PrgEnv-gnu module, which sets up correct combination of GNU compiler
+and MPI library.
+
+ $ module load PrgEnv-gnu
+
+CUDA code can be compiled directly on login1 or login2 nodes. User does
+not have to use compute nodes with GPU accelerator for compilation. To
+compile a CUDA source code, use nvcc compiler.
+
+ $ nvcc --version
+
+CUDA Toolkit comes with large number of examples, that can be
+helpful to start with. To compile and test these examples user should
+copy them to its home directoryÂ
+
+ $ cd ~
+ $ mkdir cuda-samples
+ $ cp -R /apps/nvidia/cuda/6.5.14/samples/* ~/cuda-samples/
+
+To compile an examples, change directory to the particular example (here
+the example used is deviceQuery) and run "make" to start the compilation
+
+ $ cd ~/cuda-samples/1_Utilities/deviceQuery
+ $ makeÂ
+
+To run the code user can use PBS interactive session to get access to a
+node from qnvidia queue (note: use your project name with parameter -A
+in the qsub command) and execute the binary file
+
+ $ qsub -I -q qnvidia -A OPEN-0-0
+ $ module load cuda
+ $Â ~/cuda-samples/1_Utilities/deviceQuery/deviceQuery
+
+Expected output of the deviceQuery example executed on a node with Tesla
+K20m is
+
+ CUDA Device Query (Runtime API) version (CUDART static linking)
+
+ Detected 1 CUDA Capable device(s)
+
+ Device 0: "Tesla K20m"
+ CUDA Driver Version / Runtime Version 5.0 / 5.0
+ CUDA Capability Major/Minor version number: 3.5
+ Total amount of global memory: 4800 MBytes (5032706048 bytes)
+ (13) Multiprocessors x (192) CUDA Cores/MP: 2496 CUDA Cores
+ GPU Clock rate: 706 MHz (0.71 GHz)
+ Memory Clock rate: 2600 MhzÂ
+ Memory Bus Width: 320-bit
+ L2 Cache Size: 1310720 bytes
+ Max Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536,65536), 3D=(4096,4096,4096)
+ Max Layered Texture Size (dim) x layers 1D=(16384) x 2048, 2D=(16384,16384) x 2048
+ Total amount of constant memory: 65536 bytesÂ
+ Total amount of shared memory per block: 49152 bytes
+ Total number of registers available per block: 65536
+ Warp size: 32
+ Maximum number of threads per multiprocessor: 2048
+ Maximum number of threads per block: 1024Â
+ Maximum sizes of each dimension of a block: 1024 x 1024 x 64
+ Maximum sizes of each dimension of a grid: 2147483647 x 65535 x 65535
+ Maximum memory pitch: 2147483647 bytes
+ Texture alignment: 512 bytes
+ Concurrent copy and kernel execution: Yes with 2 copy engine(s)
+ Run time limit on kernels: No
+ Integrated GPU sharing Host Memory: No
+ Support host page-locked memory mapping: Yes
+ Alignment requirement for Surfaces: YesÂ
+ Device has ECC support: EnabledÂ
+ Device supports Unified Addressing (UVA): Yes
+ Device PCI Bus ID / PCI location ID: 2 / 0
+ Compute Mode:Â
+ < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >Â
+ deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 5.0, CUDA Runtime Version = 5.0, NumDevs = 1, Device0 = Tesla K20mÂ
+
+### Code example
+
+In this section we provide a basic CUDA based vector addition code
+example. You can directly copy and paste the code to test it.Â
+
+ $ vim test.cu
+
+ #define N (2048*2048)
+ #define THREADS_PER_BLOCK 512
+
+ #include <stdio.h>
+ #include <stdlib.h>
+
+ // GPU kernel function to add two vectors
+ __global__ void add_gpu( int *a, int *b, int *c, int n){
+ Â int index = threadIdx.x + blockIdx.x * blockDim.x;
+ Â if (index < n)
+ Â c[index] = a[index] + b[index];
+ }
+
+ // CPU function to add two vectors
+ void add_cpu (int *a, int *b, int *c, int n) {
+ Â for (int i=0; i < n; i++)
+ c[i] = a[i] + b[i];
+ }
+
+ // CPU function to generate a vector of random integers
+ void random_ints (int *a, int n) {
+ Â for (int i = 0; i < n; i++)
+ Â a[i] = rand() % 10000; // random number between 0 and 9999
+ }
+
+ // CPU function to compare two vectors
+ int compare_ints( int *a, int *b, int n ){
+ Â int pass = 0;
+ Â for (int i = 0; i < N; i++){
+ Â if (a[i] != b[i]) {
+ Â printf("Value mismatch at location %d, values %d and %dn",i, a[i], b[i]);
+ Â pass = 1;
+ Â }
+ Â }
+ Â if (pass == 0) printf ("Test passedn"); else printf ("Test Failedn");
+ Â return pass;
+ }
+
+ int main( void ) {
+ Â
+ Â int *a, *b, *c; // host copies of a, b, c
+ Â int *dev_a, *dev_b, *dev_c; // device copies of a, b, c
+ Â int size = N * sizeof( int ); // we need space for N integers
+
+ Â // Allocate GPU/device copies of dev_a, dev_b, dev_c
+ Â cudaMalloc( (void**)&dev_a, size );
+ Â cudaMalloc( (void**)&dev_b, size );
+ Â cudaMalloc( (void**)&dev_c, size );
+
+ Â // Allocate CPU/host copies of a, b, c
+ Â a = (int*)malloc( size );
+ Â b = (int*)malloc( size );
+ Â c = (int*)malloc( size );
+ Â
+ Â // Fill input vectors with random integer numbers
+ Â random_ints( a, N );
+ Â random_ints( b, N );
+
+ Â // copy inputs to device
+ Â cudaMemcpy( dev_a, a, size, cudaMemcpyHostToDevice );
+ Â cudaMemcpy( dev_b, b, size, cudaMemcpyHostToDevice );
+
+ Â // launch add_gpu() kernel with blocks and threads
+ Â add_gpu<<< N/THREADS_PER_BLOCK, THREADS_PER_BLOCK >>( dev_a, dev_b, dev_c, N );
+
+ Â // copy device result back to host copy of c
+ Â cudaMemcpy( c, dev_c, size, cudaMemcpyDeviceToHost );
+
+ Â //Check the results with CPU implementation
+ Â int *c_h; c_h = (int*)malloc( size );
+ Â add_cpu (a, b, c_h, N);
+ Â compare_ints(c, c_h, N);
+
+ Â // Clean CPU memory allocations
+ Â free( a ); free( b ); free( c ); free (c_h);
+
+ Â // Clean GPU memory allocations
+ Â cudaFree( dev_a );
+ Â cudaFree( dev_b );
+ Â cudaFree( dev_c );
+
+ Â return 0;
+ }
+
+This code can be compiled using following command
+
+ $ nvcc test.cu -o test_cuda
+
+To run the code use interactive PBS session to get access to one of the
+GPU accelerated nodes
+
+ $ qsub -I -q qnvidia -A OPEN-0-0
+ $ module load cuda
+ $Â ./test.cuda
+
+CUDA Libraries
+--------------
+
+### CuBLAS
+
+The NVIDIA CUDA Basic Linear Algebra Subroutines (cuBLAS) library is a
+GPU-accelerated version of the complete standard BLAS library with 152
+standard BLAS routines. Basic description of the library together with
+basic performance comparison with MKL can be found
+[here](https://developer.nvidia.com/cublas "Nvidia cuBLAS").
+
+CuBLAS example: SAXPY**
+
+SAXPY function multiplies the vector x by the scalar alpha and adds it
+to the vector y overwriting the latest vector with the result. The
+description of the cuBLAS function can be found in [NVIDIA CUDA
+documentation](http://docs.nvidia.com/cuda/cublas/index.html#cublas-lt-t-gt-axpy "Nvidia CUDA documentation ").
+Code can be pasted in the file and compiled without any modification.
+
+ /* Includes, system */
+ #include <stdio.h>
+ #include <stdlib.h>
+
+ /* Includes, cuda */
+ #include <cuda_runtime.h>
+ #include <cublas_v2.h>
+
+ /* Vector size */
+ #define NÂ (32)
+
+ /* Host implementation of a simple version of saxpi */
+ void saxpy(int n, float alpha, const float *x, float *y)
+ {
+ Â Â Â for (int i = 0; i < n; ++i)
+ Â Â Â y[i] = alpha*x[i] + y[i];
+ }
+
+ /* Main */
+ int main(int argc, char **argv)
+ {
+ Â Â Â float *h_X, *h_Y, *h_Y_ref;
+ Â Â Â float *d_X = 0;
+ Â Â Â float *d_Y = 0;
+
+ Â Â Â const float alpha = 1.0f;
+ Â Â Â int i;
+
+ Â Â Â cublasHandle_t handle;
+
+ Â Â Â /* Initialize CUBLAS */
+ Â Â Â printf("simpleCUBLAS test running..n");
+ Â Â Â cublasCreate(&handle);
+
+ Â Â Â /* Allocate host memory for the matrices */
+ Â Â Â h_X = (float *)malloc(N * sizeof(h_X[0]));
+ Â Â Â h_Y = (float *)malloc(N * sizeof(h_Y[0]));
+ Â Â Â h_Y_ref = (float *)malloc(N * sizeof(h_Y_ref[0]));
+
+ Â Â Â /* Fill the matrices with test data */
+ Â Â Â for (i = 0; i < N; i++)
+ Â Â Â {
+ Â Â Â Â Â Â Â h_X[i] = rand() / (float)RAND_MAX;
+ Â Â Â Â Â Â Â h_Y[i] = rand() / (float)RAND_MAX;
+ Â Â Â Â Â Â Â h_Y_ref[i] = h_Y[i];
+ Â Â Â }
+
+ Â Â Â /* Allocate device memory for the matrices */
+ Â Â Â cudaMalloc((void **)&d_X, N * sizeof(d_X[0]));
+ Â Â Â cudaMalloc((void **)&d_Y, N * sizeof(d_Y[0]));
+
+ Â Â Â /* Initialize the device matrices with the host matrices */
+ Â Â Â cublasSetVector(N, sizeof(h_X[0]), h_X, 1, d_X, 1);
+ Â Â Â cublasSetVector(N, sizeof(h_Y[0]), h_Y, 1, d_Y, 1);
+
+ Â Â Â /* Performs operation using plain C code */
+ Â Â Â saxpy(N, alpha, h_X, h_Y_ref);
+
+ Â Â Â /* Performs operation using cublas */
+ Â Â Â cublasSaxpy(handle, N, &alpha, d_X, 1, d_Y, 1);
+
+ Â Â Â /* Read the result back */
+ Â Â Â cublasGetVector(N, sizeof(h_Y[0]), d_Y, 1, h_Y, 1);
+
+ Â Â Â /* Check result against reference */
+ Â Â Â for (i = 0; i < N; ++i)
+ Â Â Â Â Â Â Â printf("CPU res = %f t GPU res = %f t diff = %f n", h_Y_ref[i], h_Y[i], h_Y_ref[i] - h_Y[i]);
+
+ Â Â Â /* Memory clean up */
+ Â Â Â free(h_X); free(h_Y); free(h_Y_ref);
+ Â Â Â cudaFree(d_X); cudaFree(d_Y);
+
+ Â Â Â /* Shutdown */
+ Â Â Â cublasDestroy(handle);
+ }
+
+Â Please note: cuBLAS has its own function for data transfers between CPU
+and GPU memory:
+Â -
+[cublasSetVector](http://docs.nvidia.com/cuda/cublas/index.html#cublassetvector)
+- transfers data from CPU to GPU memory
+Â -
+[cublasGetVector](http://docs.nvidia.com/cuda/cublas/index.html#cublasgetvector)
+- transfers data from GPU to CPU memory
+
+Â To compile the code using NVCC compiler a "-lcublas" compiler flag has
+to be specified:
+
+ $ module load cuda
+ $ nvcc -lcublas test_cublas.cu -o test_cublas_nvcc
+
+To compile the same code with GCC:
+
+ $ module load cuda
+ $ gcc -std=c99 test_cublas.c -o test_cublas_icc -lcublas -lcudart
+
+To compile the same code with Intel compiler:
+
+ $ module load cuda intel
+ $ icc -std=c99 test_cublas.c -o test_cublas_icc -lcublas -lcudart
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/omics-master-1/diagnostic-component-team.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/omics-master-1/diagnostic-component-team.md
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@@ -0,0 +1,49 @@
+Diagnostic component (TEAM)
+===========================
+
+
+
+### Access
+
+TEAM is available at the following address
+:Â <http://omics.it4i.cz/team/>
+
+The address is accessible only via
+[VPN. ](../../accessing-the-cluster/vpn-access.html)
+
+### Diagnostic component (TEAM) {#diagnostic-component-team}
+
+VCF files are scanned by this diagnostic tool for known diagnostic
+disease-associated variants. When no diagnostic mutation is found, the
+file can be sent to the disease-causing gene discovery tool to see
+wheter new disease associated variants can be found.
+
+TEAMÂ >(27)Â is an intuitive and easy-to-use web tool that
+fills the gap between the predicted mutations and the final diagnostic
+in targeted enrichment sequencing analysis. The tool searches for known
+diagnostic mutations, corresponding to a disease panel, among the
+predicted patient’s variants. Diagnostic variants for the disease are
+taken from four databases of disease-related variants (HGMD-public,
+HUMSAVAR , ClinVar and COSMIC) If no primary diagnostic variant is
+found, then a list of secondary findings that can help to establish a
+diagnostic is produced. TEAM also provides with an interface for the
+definition of and customization of panels, by means of which, genes and
+mutations can be added or discarded to adjust panel definitions.Â
+
+
+
+Â
+
+*Figure 5. ***Interface of the application. Panels for defining
+targeted regions of interest can be set up by just drag and drop known
+disease genes or disease definitions from the lists. Thus, virtual
+panels can be interactively improved as the knowledge of the disease
+increases.*
+
+*
+*
+
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@@ -0,0 +1,827 @@
+Overview
+========
+
+The human NGS data processing solution
+
+
+
+Introduction
+------------
+
+The scope of this OMICS MASTER solution is restricted to human genomics
+research (disease causing gene discovery in whole human genome or exome)
+or diagnosis (panel sequencing), although it could be extended in the
+future to other usages.
+
+The pipeline inputs the raw data produced by the sequencing machines and
+undergoes a processing procedure that consists on a quality control, the
+mapping and variant calling steps that result in a file containing the
+set of variants in the sample. From this point, the prioritization
+component or the diagnostic component can be launched.Â
+
+
+
+*Figure 1.** *OMICS MASTER solution overview. Data is produced in the
+external labs and comes to IT4I (represented by the blue dashed line).
+The data pre-processor converts raw data into a list of variants and
+annotations for each sequenced patient. These lists files together with
+primary and secondary (alignment) data files are stored in IT4I sequence
+DB and uploaded to the discovery (candidate prioritization) or
+diagnostic component where they can be analyzed directly by the user
+that produced them, depending of the experimental design carried
+out*. style="text-align: left; ">Â
+
+Typical genomics pipelines are composed by several components that need
+to be launched manually. The advantage of OMICS MASTER pipeline is that
+all these components are invoked sequentially in an automated way.
+
+OMICS MASTER pipeline inputs a FASTQ file and outputs an enriched VCF
+file. This pipeline is able to queue all the jobs to PBS by only
+launching a process taking all the necessary input files and creates the
+intermediate and final folders
+
+Let’s see each of the OMICS MASTER solution components:
+
+Components
+----------
+
+### Processing
+
+This component is composed by a set of programs that carry out quality
+controls, alignment, realignment, variant calling and variant
+annotation. It turns raw data from the sequencing machine into files
+containing lists of variants (VCF) that once annotated, can be used by
+the following components (discovery and diagnosis).
+
+We distinguish three types of sequencing instruments: bench sequencers
+(MySeq, IonTorrent, and Roche Junior, although this last one is about
+being discontinued), which produce relatively Genomes in the clinic
+
+low throughput (tens of million reads), and high end sequencers, which
+produce high throughput (hundreds of million reads) among which we have
+Illumina HiSeq 2000 (and new models) and SOLiD. All of them but SOLiD
+produce data in sequence format. SOLiD produces data in a special format
+called colour space that require of specific software for the mapping
+process. Once the mapping has been done, the rest of the pipeline is
+identical. Anyway, SOLiD is a technology which is also about being
+discontinued by the manufacturer so, this type of data will be scarce in
+the future.
+
+#### Quality control, preprocessing and statistics for FASTQ
+
+ FastQC& FastQC.
+
+These steps are carried out over the original FASTQ file with optimized
+scripts and includes the following steps: sequence cleansing, estimation
+of base quality scores, elimination of duplicates and statistics.
+
+Input: FASTQ file.
+
+Output: FASTQ file plus an HTML file containing statistics on the
+data.Â
+
+FASTQ formatÂ
+It represents the nucleotide sequence and its corresponding
+quality scores.
+
+
+*Figure 2.**FASTQ file.**
+
+#### Mapping
+
+Component:** Hpg-aligner.**
+
+Sequence reads are mapped over the human reference genome. SOLiD reads
+are not covered by this solution; they should be mapped with specific
+software (among the few available options, SHRiMP seems to be the best
+one). For the rest of NGS machine outputs we use HPG Aligner.
+HPG-Aligner is an innovative solution, based on a combination of mapping
+with BWT and local alignment with Smith-Waterman (SW), that drastically
+increases mapping accuracy (97% versus 62-70% by current mappers, in the
+most common scenarios). This proposal provides a simple and fast
+solution that maps almost all the reads, even those containing a high
+number of mismatches or indels.
+
+Input: FASTQ file.
+
+Output:** Aligned file in BAM format.***
+
+Sequence Alignment/Map (SAM)**
+
+It is a human readable tab-delimited format in which each read and
+its alignment is represented on a single line. The format can represent
+unmapped reads, reads that are mapped to unique locations, and reads
+that are mapped to multiple locations.
+
+The SAM format (1)^> consists of one header
+section and one alignment section. The lines in the header section start
+with character â€@’, and lines in the alignment section do not. All lines
+are TAB delimited.
+
+In SAM, each alignment line has 11 mandatory fields and a variable
+number of optional fields. The mandatory fields are briefly described in
+Table 1. They must be present but their value can be a
+â€*’> or a zero (depending on the field) if the
+corresponding information is unavailable. Â
+
+<col width="33%" />
+<col width="33%" />
+<col width="33%" />
+ |<strong>No.</strong>\ |<p><strong>Name</strong>\ |<p><strong>Description</strong></p> |
+ |1\ |<p>QNAME\ |<p>Query NAME of the read or the read pair</p> |
+ |2\ |<p>FLAG\ |<p>Bitwise FLAG (pairing,strand,mate strand,etc.)</p> |
+ |3\ |<p>RNAMEÂ \ |<p>Reference sequence NAME</p> |
+ |4\ |<p>POS \ |<p>1-Based  leftmost POSition of clipped alignment</p> |
+ |5\ |<p>MAPQÂ \ |<p>MAPping Quality (Phred-scaled)</p> |
+ |6\ |<p>CIGARÂ \ |<p>Extended CIGAR string (operations:MIDNSHP)</p> |
+ |7\ |<p>MRNMÂ \ |<p>Mate REference NaMe ('=' if same RNAME)</p> |
+ |8\ |<p>MPOSÂ \ |<p>1-Based leftmost Mate POSition</p> |
+ |9\ |<p>ISIZEÂ \ |<p>Inferred Insert SIZEÂ </p> |
+ |10\ |<p>SEQÂ \ |<p>Query SEQuence on the same strand as the reference</p> |
+ |11\ |<p>QUALÂ \ |<p>Query QUALity (ASCII-33=Phred base quality)</p> |
+
+*Table 1.** *Mandatory fields in the SAM format.
+
+The standard CIGAR description of pairwise alignment defines three
+operations: â€M’ for match/mismatch, â€I’ for insertion compared with the
+reference and â€D’ for deletion. The extended CIGAR proposed in SAM added
+four more operations: â€N’ for skipped bases on the reference, â€S’ for
+soft clipping, â€H’ for hard clipping and â€P’ for padding. These support
+splicing, clipping, multi-part and padded alignments. Figure 3 shows
+examples of CIGAR strings for different types of alignments.Â
+
+
+*
+Figure 3.** *SAM format file. The â€@SQ’ line in the header section
+gives the order of reference sequences. Notably, r001 is the name of a
+read pair. According to FLAG 163 (=1+2+32+128), the read mapped to
+position 7 is the second read in the pair (128) and regarded as properly
+paired (1 + 2); its mate is mapped to 37 on the reverse strand (32).
+Read r002 has three soft-clipped (unaligned) bases. The coordinate shown
+in SAM is the position of the first aligned base. The CIGAR string for
+this alignment contains a P (padding) operation which correctly aligns
+the inserted sequences. Padding operations can be absent when an aligner
+does not support multiple sequence alignment. The last six bases of read
+r003 map to position 9, and the first five to position 29 on the reverse
+strand. The hard clipping operation H indicates that the clipped
+sequence is not present in the sequence field. The NM tag gives the
+number of mismatches. Read r004 is aligned across an intron, indicated
+by the N operation.**
+
+Binary Alignment/Map (BAM)**
+
+BAM is the binary representation of SAM and keeps exactly the same
+information as SAM. BAM uses lossless compression to reduce the size of
+the data by about 75% and provides an indexing system that allows reads
+that overlap a region of the genome to be retrieved and rapidly
+traversed.Â
+
+#### Quality control, preprocessing and statistics for BAM
+
+Component:** Hpg-Fastq & FastQC. Some features:
+
+- Quality control: % reads with N errors, % reads with multiple
+ mappings, strand bias, paired-end insert, ...
+- Filtering: by number of errors, number of hits, …
+ - Comparator: stats, intersection, ...
+
+Input:** BAM** file.**
+
+Output:** BAM file plus an HTML file containing statistics.**
+
+#### Variant Calling
+
+Component:** GATK.**
+
+Identification of single nucleotide variants and indels on the
+alignments is performed using the Genome Analysis Toolkit (GATK). GATK
+(2)^ is a software package developed at the Broad Institute to analyze
+high-throughput sequencing data. The toolkit offers a wide variety of
+tools, with a primary focus on variant discovery and genotyping as well
+as strong emphasis on data quality assurance.
+
+Input:** BAM**
+
+Output:** VCF**
+
+**Variant Call Format (VCF)**
+
+VCF (3)^> is a standardized format for storing the
+most prevalent types of sequence variation, including SNPs, indels and
+larger structural variants, together with rich annotations. The format
+was developed with the primary intention to represent human genetic
+variation, but its use is not restricted >to diploid genomes
+and can be used in different contexts as well. Its flexibility and user
+extensibility allows representation of a wide variety of genomic
+variation with respect to a single reference sequence.
+
+A VCF file consists of a header section and a data section. The
+header contains an arbitrary number of metainformation lines, each
+starting with characters â€##’, and a TAB delimited field definition
+line, starting with a single â€#’ character. The meta-information header
+lines provide a standardized description of tags and annotations used in
+the data section. The use of meta-information allows the information
+stored within a VCF file to be tailored to the dataset in question. It
+can be also used to provide information about the means of file
+creation, date of creation, version of the reference sequence, software
+used and any other information relevant to the history of the file. The
+field definition line names eight mandatory columns, corresponding to
+data columns representing the chromosome (CHROM), a 1-based position of
+the start of the variant (POS), unique identifiers of the variant (ID),
+the reference allele (REF), a comma separated list of alternate
+non-reference alleles (ALT), a phred-scaled quality score (QUAL), site
+filtering information (FILTER) and a semicolon separated list of
+additional, user extensible annotation (INFO). In addition, if samples
+are present in the file, the mandatory header columns are followed by a
+FORMAT column and an arbitrary number of sample IDs that define the
+samples included in the VCF file. The FORMAT column is used to defineÂ
+the information contained within each subsequent genotype column, which
+consists of a colon separated list of fields. For example, the FORMAT
+field GT:GQ:DP in the fourth data entry of Figure 1a indicates that the
+subsequent entries contain information regarding the genotype, genotype
+quality and read depth for each sample. All data lines are TAB
+delimited and the number of fields in each data line must match the
+number of fields in the header line. It is strongly recommended that all
+annotation tags used are declared in the VCF header section.
+
+
+
+Figure 4.**> (a) Example of valid VCF. The header lines
+##fileformat and #CHROM are mandatory, the rest is optional but
+strongly recommended. Each line of the body describes variants present
+in the sampled population at one genomic position or region. All
+alternate alleles are listed in the ALT column and referenced from the
+genotype fields as 1-based indexes to this list; the reference haplotype
+is designated as 0. For multiploid data, the separator indicates whether
+the data are phased (|) or unphased (/). Thus, the two alleles C and G
+at the positions 2 and 5 in this figure occur on the same chromosome in
+SAMPLE1. The first data line shows an example of a deletion (present in
+SAMPLE1) and a replacement of two bases by another base (SAMPLE2); the
+second line shows a SNP and an insertion; the third a SNP; the fourth a
+large structural variant described by the annotation in the INFO column,
+the coordinate is that of the base before the variant. (b–f ) Alignments
+and VCF representations of different sequence variants: SNP, insertion,
+deletion, replacement, and a large deletion. The REF columns shows the
+reference bases replaced by the haplotype in the ALT column. The
+coordinate refers to the first reference base. (g) Users are advised to
+use simplest representation possible and lowest coordinate in cases
+where the position is ambiguous.
+
+###Annotating
+
+Component:** HPG-Variant
+
+The functional consequences of every variant found are then annotated
+using the HPG-Variant software, which extracts from CellBase**,** the
+Knowledge database, all the information relevant on the predicted
+pathologic effect of the variants.
+
+VARIANT (VARIant Analysis Tool) (4)^ reports information on the
+variants found that include consequence type and annotations taken from
+different databases and repositories (SNPs and variants from dbSNP and
+1000 genomes, and disease-related variants from the Genome-Wide
+Association Study (GWAS) catalog, Online Mendelian Inheritance in Man
+(OMIM), Catalog of Somatic Mutations in Cancer (COSMIC) mutations, etc.
+VARIANT also produces a rich variety of annotations that include
+information on the regulatory (transcription factor or miRNAbinding
+sites, etc.) or structural roles, or on the selective pressures on the
+sites affected by the variation. This information allows extending the
+conventional reports beyond the coding regions and expands the knowledge
+on the contribution of non-coding or synonymous variants to the
+phenotype studied.
+
+Input:** VCF**
+
+Output:** The output of this step is the Variant Calling Format (VCF)
+file, which contains changes with respect to the reference genome with
+the corresponding QC and functional annotations.**
+
+#### CellBase
+
+CellBase(5)^Â is a relational database integrates biological information
+from different sources and includes:
+
+**Core features:**
+
+We took genome sequences, genes, transcripts, exons, cytobands or cross
+references (xrefs) identifiers (IDs)Â >from Ensembl
+(6)^>. Protein information including sequences, xrefs or
+protein features (natural variants, mutagenesis sites,
+post-translational modifications, etc.) were imported from UniProt
+(7)^>.
+
+**Regulatory:**
+
+CellBase imports miRNA from miRBase (8)^; curated and non-curated miRNA
+targets from miRecords (9)^, >miRTarBase ^(10)^>,
+TargetScan(11)^> and microRNA.org ^(12)^> and
+CpG islands and conserved regions from the UCSC database
+(13)^>.>
+
+**Functional annotation**
+
+OBO Foundry (14)^ develops many biomedical ontologies that are
+implemented in OBO format. We designed a SQL schema to store these OBO
+ontologies and >30 ontologies were imported. OBO ontology term
+annotations were taken from Ensembl (6)^. InterPro ^(15)^ annotations
+were also imported.
+
+**Variation**
+
+CellBase includes SNPs from dbSNP (16)^; SNP population frequencies
+from HapMap (17)^, 1000 genomes project ^(18)^ and Ensembl ^(6)^;
+phenotypically annotated SNPs were imported from NHRI GWAS Catalog
+(19)^,^Â ^>HGMD ^(20)^>, Open Access GWAS Database
+(21)^>, UniProt ^(7)^> and OMIM
+(22)^>; mutations from COSMICÂ ^(23)^> and
+structural variations from Ensembl
+(6)^>.>
+
+**Systems biology**
+
+We also import systems biology information like interactome information
+from IntAct (24)^. Reactome ^(25)^> stores pathway and interaction
+information in BioPAX (26)^> format. BioPAX data exchange
+format >enables the integration of diverse pathway
+resources. We successfully solved the problem of storing data released
+in BioPAX format into a SQL relational schema, which allowed us
+importing Reactome in CellBase.
+
+### [Diagnostic component (TEAM)](diagnostic-component-team.html)
+
+### [Priorization component (BiERApp)](priorization-component-bierapp.html)
+
+Usage
+-----
+
+First of all, we should load ngsPipeline
+module:
+
+ $ module load ngsPipeline
+
+This command will load python/2.7.5
+module and all the required modules (
+hpg-aligner,
+gatk, etc)
+
+ If we launch ngsPipeline with â€-h’, we will get the usage
+help:Â
+
+ $ ngsPipeline -h
+ Usage: ngsPipeline.py [-h] -i INPUT -o OUTPUT -p PED --project PROJECT --queue
+ Â Â Â Â Â Â Â Â Â Â Â QUEUE [--stages-path STAGES_PATH] [--email EMAIL]
+ [--prefix PREFIX] [-s START] [-e END] --log
+
+ Python pipeline
+
+ optional arguments:
+  -h, --help       show this help message and exit
+ Â -i INPUT, --input INPUT
+ Â -o OUTPUT, --output OUTPUT
+ Â Â Â Â Â Â Â Â Â Â Â Â Output Data directory
+ Â -p PED, --ped PED Â Â Ped file with all individuals
+ Â --project PROJECT Â Â Project Id
+ Â --queue QUEUE Â Â Â Â Queue Id
+ Â --stages-path STAGES_PATH
+ Â Â Â Â Â Â Â Â Â Â Â Â Custom Stages path
+ Â --email EMAIL Â Â Â Â Email
+ Â --prefix PREFIX Â Â Â Prefix name for Queue Jobs name
+ Â -s START, --start START
+ Â Â Â Â Â Â Â Â Â Â Â Â Initial stage
+ Â -e END, --end END Â Â Final stage
+  --log         Log to file
+
+Â
+
+Let us see a brief description of the arguments:
+
+Â Â Â Â Â *-h --help*. Show the help.
+
+Â Â Â Â Â *-i, --input.* The input data directory. This directory must to
+have a special structure. We have to create one folder per sample (with
+the same name). These folders will host the fastq files. These fastq
+files must have the following pattern “sampleName” + “_” + “1 or 2” +
+“.fq”. 1 for the first pair (in paired-end sequences), and 2 for the
+second one.
+
+Â Â Â Â Â *-o , --output.* The output folder. This folder will contain all
+the intermediate and final folders. When the pipeline will be executed
+completely, we could remove the intermediate folders and keep only the
+final one (with the VCF file containing all the variants)
+
+Â Â Â Â Â *-p , --ped*. The ped file with the pedigree. This file contains
+all the sample names. These names must coincide with the names of the
+input folders. If our input folder contains more samples than the .ped
+file, the pipeline will use only the samples from the .ped file.
+
+Â Â Â Â Â *--email.* Email for PBS notifications.
+
+Â Â Â Â Â *--prefix.* Prefix for PBS Job names.
+
+Â Â Â Â *-s, --start & -e, --end.* Â Initial and final stage. If we want to
+launch the pipeline in a specific stage we must use -s. If we want to
+end the pipeline in a specific stage we must use -e.
+
+Â Â Â Â Â *--log*. Using log argument NGSpipeline will prompt all the logs
+to this file.
+
+Â Â Â Â *--project*>. Project ID of your supercomputer
+allocation.Â
+
+Â Â Â Â *--queue*.
+[Queue](../../resource-allocation-and-job-execution/introduction.html)
+to run the jobs in.
+
+Â >Input, output and ped arguments are mandatory. If the output
+folder does not exist, the pipeline will create it.
+
+Examples
+---------------------
+
+This is an example usage of NGSpipeline:
+
+We have a folder with the following structure in >
+/apps/bio/omics/1.0/sample_data/Â >:
+
+ /apps/bio/omics/1.0/sample_data
+ └── data
+ ├── file.ped
+ ├── sample1
+ │  ├── sample1_1.fq
+ │  └── sample1_2.fq
+ └── sample2
+ ├── sample2_1.fq
+ └── sample2_2.fq
+
+The ped file ( file.ped) contains the
+following info:>Â
+
+ #family_ID sample_ID parental_ID maternal_ID sex phenotype
+ FAM sample_A 0 0 1 1
+ FAM sample_B 0 0 2 2
+
+Now, lets load the NGSPipeline module and copy the sample data to a
+[scratch directory](../../storage.html) :
+
+ $ module load ngsPipeline
+ $ mkdir -p /scratch/$USER/omics/results
+ $ cp -r /apps/bio/omics/1.0/sample_data /scratch/$USER/omics/
+
+Now, we can launch the pipeline (replace OPEN-0-0 with your Project ID)
+:
+
+ $ ngsPipeline -i /scratch/$USER/omics/sample_data/data -o /scratch/$USER/omics/results -p /scratch/$USER/omics/sample_data/data/file.ped --project OPEN-0-0 --queue qprod
+
+This command submits the processing [jobs to the
+queue](../../resource-allocation-and-job-execution/job-submission-and-execution.html).Â
+
+If we want to re-launch the pipeline from stage 4 until stage 20 we
+should use the next command:
+
+ $ ngsPipeline -i /scratch/$USER/omics/sample_data/data -o /scratch/$USER/omics/results -p /scratch/$USER/omics/sample_data/data/file.ped -s 4 -e 20 --project OPEN-0-0 --queue qprod
+
+Details on the pipeline
+------------------------------------
+
+The pipeline calls the following tools:
+
+- >[fastqc](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/),
+ a>Â quality control tool for high throughput
+ sequence data.
+- >[gatk](https://www.broadinstitute.org/gatk/), >The
+ Genome Analysis Toolkit or GATK is a software package developed at
+ the Broad Institute to analyze high-throughput sequencing data. The
+ toolkit offers a wide variety of tools, with a primary focus on
+ variant discovery and genotyping as well as strong emphasis on data
+ quality assurance. Its robust architecture, powerful processing
+ engine and high-performance computing features make it capable of
+ taking on projects of any size.
+- >[hpg-aligner](http://wiki.opencb.org/projects/hpg/doku.php?id=aligner:downloads), >HPG
+ Aligner has been designed to align short and long reads with high
+ sensitivity, therefore any number of mismatches or indels
+ are allowed. HPG Aligner implements and combines two well known
+ algorithms:Â *Burrows-Wheeler Transform*>Â (BWT) to
+ speed-up mapping high-quality reads,
+ and *Smith-Waterman*> (SW) to increase sensitivity when
+ reads cannot be mapped using BWT.
+- >[hpg-fastq](http://docs.bioinfo.cipf.es/projects/fastqhpc/wiki), > a
+ quality control tool for high throughput
+ sequence data.
+- >[hpg-variant](http://wiki.opencb.org/projects/hpg/doku.php?id=variant:downloads), >The
+ HPG Variant suite is an ambitious project aimed to provide a
+ complete suite of tools to work with genomic variation data, from
+ VCF tools to variant profiling or genomic statistics. It is being
+ implemented using High Performance Computing technologies to provide
+ the best performance possible.
+- >[picard](http://picard.sourceforge.net/), >Picard
+ comprises Java-based command-line utilities that manipulate SAM
+ files, and a Java API (HTSJDK) for creating new programs that read
+ and write SAM files. Both SAM text format and SAM binary (BAM)
+ format are supported.
+- >[samtools](http://samtools.sourceforge.net/samtools-c.shtml), >SAM
+ Tools provide various utilities for manipulating alignments in the
+ SAM format, including sorting, merging, indexing and generating
+ alignments in a
+ per-position format.
+- >>[snpEff](http://snpeff.sourceforge.net/), <span>Genetic
+ variant annotation and effect
+ prediction toolbox.
+
+This listing show which tools are used in each step of the pipeline :
+
+- >stage-00: fastqc
+- >stage-01: hpg_fastq
+- >stage-02: fastqc
+- >stage-03: hpg_aligner and samtools
+- >stage-04: samtools
+- >stage-05: samtools
+- >stage-06: fastqc
+- >stage-07: picard
+- >stage-08: fastqc
+- >stage-09: picard
+- >stage-10: gatk
+- >stage-11: gatk
+- >stage-12: gatk
+- >stage-13: gatk
+- >stage-14: gatk
+- >stage-15: gatk
+- >stage-16: samtools
+- >stage-17: samtools
+- >stage-18: fastqc
+- >stage-19: gatk
+- >stage-20: gatk
+- >stage-21: gatk
+- >stage-22: gatk
+- >stage-23: gatk
+- >stage-24: hpg-variant
+- >stage-25: hpg-variant
+- >stage-26: snpEff
+- >stage-27: snpEff
+- >stage-28: hpg-variant
+
+Interpretation
+---------------------------
+
+The output folder contains all the subfolders with the intermediate
+data. This folder contains the final VCF with all the variants. This
+file can be uploaded into
+[TEAM](diagnostic-component-team.html) by using the VCF
+file button. It is important to note here that the entire management of
+the VCF file is local: no patient’s sequence data is sent over the
+Internet thus avoiding any problem of data privacy or confidentiality.
+
+
+
+*Figure 7**. *TEAM upload panel.* *Once the file has been uploaded, a
+panel must be chosen from the Panel *** list. Then, pressing the Run
+button the diagnostic process starts.*
+
+Once the file has been uploaded, a panel must be chosen from the Panel
+list. Then, pressing the Run button the diagnostic process starts. TEAM
+searches first for known diagnostic mutation(s) taken from four
+databases: HGMD-public (20)^,
+[HUMSAVAR](http://www.uniprot.org/docs/humsavar),
+ClinVar (29)^ and COSMIC ^(23)^.
+
+
+
+*Figure 7.** *The panel manager. The elements used to define a panel
+are (**A**) disease terms, (**B**) diagnostic mutations and (**C**)
+genes. Arrows represent actions that can be taken in the panel manager.
+Panels can be defined by using the known mutations and genes of a
+particular disease. This can be done by dragging them to the **Primary
+Diagnostic** box (action **D**). This action, in addition to defining
+the diseases in the **Primary Diagnostic** box, automatically adds the
+corresponding genes to the **Genes** box. The panels can be customized
+by adding new genes (action **F**) or removing undesired genes (action
+G**). New disease mutations can be added independently or associated
+to an already existing disease term (action **E**). Disease terms can be
+removed by simply dragging them back (action **H**).*
+
+For variant discovering/filtering we should upload the VCF file into
+BierApp by using the following form:
+
+**
+
+**Figure 8.** *BierApp VCF upload panel. It is recommended to choose
+a name for the job as well as a description.**
+
+Each prioritization (â€job’) has three associated screens that facilitate
+the filtering steps. The first one, the â€Summary’ tab, displays a
+statistic of the data set analyzed, containing the samples analyzed, the
+number and types of variants found and its distribution according to
+consequence types. The second screen, in the â€Variants and effect’ tab,
+is the actual filtering tool, and the third one, the â€Genome view’ tab,
+offers a representation of the selected variants within the genomic
+context provided by an embedded version of >the Genome Maps Tool
+(30)^>.
+
+
+
+**Figure 9.*** *This picture shows all the information associated to
+the variants. If a variant has an associated phenotype we could see it
+in the last column. In this case, the variant 7:132481242 C>T is
+associated to the phenotype: large intestine tumor.**
+
+*
+*
+
+References
+-----------------------
+
+1. Heng Li, Bob Handsaker, Alec Wysoker, Tim
+ Fennell, Jue Ruan, Nils Homer, Gabor Marth5, Goncalo Abecasis6,
+ Richard Durbin and 1000 Genome Project Data Processing Subgroup: The
+ Sequence Alignment/Map format and SAMtools. Bioinformatics 2009,
+ 25: 2078-2079.
+2. >McKenna A, Hanna M, Banks E, Sivachenko
+ A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S,
+ Daly M, DePristo MA: The Genome Analysis Toolkit: a MapReduce
+ framework for analyzing next-generation DNA sequencing data.
+ *Genome Res* >2010, 20:1297-1303.
+3. Petr Danecek, Adam Auton, Goncalo Abecasis,
+ Cornelis A. Albers, Eric Banks, Mark A. DePristo, Robert E.
+ Handsaker, Gerton Lunter, Gabor T. Marth, Stephen T. Sherry, Gilean
+ McVean, Richard Durbin, and 1000 Genomes Project Analysis Group. The
+ variant call format and VCFtools. Bioinformatics 2011,
+ 27: 2156-2158.
+4. Medina I, De Maria A, Bleda M, Salavert F,
+ Alonso R, Gonzalez CY, Dopazo J: VARIANT: Command Line, Web service
+ and Web interface for fast and accurate functional characterization
+ of variants found by Next-Generation Sequencing. Nucleic Acids Res
+ 2012, 40:W54-58.
+5. Bleda M, Tarraga J, de Maria A, Salavert F,
+ Garcia-Alonso L, Celma M, Martin A, Dopazo J, Medina I: CellBase, a
+ comprehensive collection of RESTful web services for retrieving
+ relevant biological information from heterogeneous sources. Nucleic
+ Acids Res 2012, 40:W609-614.
+6. Flicek,P., Amode,M.R., Barrell,D., Beal,K.,
+ Brent,S., Carvalho-Silva,D., Clapham,P., Coates,G.,
+ Fairley,S., Fitzgerald,S. et al. (2012) Ensembl 2012. Nucleic Acids
+ Res., 40, D84–D90.
+7. UniProt Consortium. (2012) Reorganizing the
+ protein space at the Universal Protein Resource (UniProt). Nucleic
+ Acids Res., 40, D71–D75.
+8. Kozomara,A. and Griffiths-Jones,S. (2011)
+ miRBase: integrating microRNA annotation and deep-sequencing data.
+ Nucleic Acids Res., 39, D152–D157.
+9. Xiao,F., Zuo,Z., Cai,G., Kang,S., Gao,X.
+ and Li,T. (2009) miRecords: an integrated resource for
+ microRNA-target interactions. Nucleic Acids Res.,
+ 37, D105–D110.
+10. Hsu,S.D., Lin,F.M., Wu,W.Y., Liang,C.,
+ Huang,W.C., Chan,W.L., Tsai,W.T., Chen,G.Z., Lee,C.J., Chiu,C.M.
+ et al. (2011) miRTarBase: a database curates experimentally
+ validated microRNA-target interactions. Nucleic Acids Res.,
+ 39, D163–D169.
+11. Friedman,R.C., Farh,K.K., Burge,C.B.
+ and Bartel,D.P. (2009) Most mammalian mRNAs are conserved targets
+ of microRNAs. Genome Res., 19, 92–105.
+12. Betel,D., Wilson,M., Gabow,A., Marks,D.S.
+ and Sander,C. (2008) The microRNA.org resource: targets
+ and expression. Nucleic Acids Res., 36, D149–D153.
+13. Dreszer,T.R., Karolchik,D., Zweig,A.S.,
+ Hinrichs,A.S., Raney,B.J., Kuhn,R.M., Meyer,L.R., Wong,M.,
+ Sloan,C.A., Rosenbloom,K.R. et al. (2012) The UCSC genome browser
+ database: extensions and updates 2011. Nucleic Acids Res.,
+ 40, D918–D923.
+14. Smith,B., Ashburner,M., Rosse,C., Bard,J.,
+ Bug,W., Ceusters,W., Goldberg,L.J., Eilbeck,K.,
+ Ireland,A., Mungall,C.J. et al. (2007) The OBO Foundry: coordinated
+ evolution of ontologies to support biomedical data integration. Nat.
+ Biotechnol., 25, 1251–1255.
+15. Hunter,S., Jones,P., Mitchell,A.,
+ Apweiler,R., Attwood,T.K.,Bateman,A., Bernard,T., Binns,D.,
+ Bork,P., Burge,S. et al. (2012) InterPro in 2011: new developments
+ in the family and domain prediction database. Nucleic Acids Res.,
+ 40, D306–D312.
+16. Sherry,S.T., Ward,M.H., Kholodov,M.,
+ Baker,J., Phan,L., Smigielski,E.M. and Sirotkin,K. (2001) dbSNP: the
+ NCBI database of genetic variation. Nucleic Acids Res.,
+ 29, 308–311.
+17. Altshuler,D.M., Gibbs,R.A., Peltonen,L.,
+ Dermitzakis,E., Schaffner,S.F., Yu,F., Bonnen,P.E., de Bakker,P.I.,
+ Deloukas,P., Gabriel,S.B. et al. (2010) Integrating common and rare
+ genetic variation in diverse human populations. Nature,
+ 467, 52–58.
+18. 1000 Genomes Project Consortium. (2010) A map
+ of human genome variation from population-scale sequencing. Nature,
+ 467, 1061–1073.
+19. Hindorff,L.A., Sethupathy,P., Junkins,H.A.,
+ Ramos,E.M., Mehta,J.P., Collins,F.S. and Manolio,T.A. (2009)
+ Potential etiologic and functional implications of genome-wide
+ association loci for human diseases and traits. Proc. Natl Acad.
+ Sci. USA, 106, 9362–9367.
+20. Stenson,P.D., Ball,E.V., Mort,M.,
+ Phillips,A.D., Shiel,J.A., Thomas,N.S., Abeysinghe,S., Krawczak,M.
+ and Cooper,D.N. (2003) Human gene mutation database (HGMD):
+ 2003 update. Hum. Mutat., 21, 577–581.
+21. Johnson,A.D. and O’Donnell,C.J. (2009) An
+ open access database of genome-wide association results. BMC Med.
+ Genet, 10, 6.
+22. McKusick,V. (1998) A Catalog of Human Genes
+ and Genetic Disorders, 12th edn. John Hopkins University
+ Press,Baltimore, MD.
+23. Forbes,S.A., Bindal,N., Bamford,S., Cole,C.,
+ Kok,C.Y., Beare,D., Jia,M., Shepherd,R., Leung,K., Menzies,A. et al.
+ (2011) COSMIC: mining complete cancer genomes in the catalogue of
+ somatic mutations in cancer. Nucleic Acids Res.,
+ 39, D945–D950.
+24. Kerrien,S., Aranda,B., Breuza,L., Bridge,A.,
+ Broackes-Carter,F., Chen,C., Duesbury,M., Dumousseau,M.,
+ Feuermann,M., Hinz,U. et al. (2012) The Intact molecular interaction
+ database in 2012. Nucleic Acids Res., 40, D841–D846.
+25. Croft,D., O’Kelly,G., Wu,G., Haw,R.,
+ Gillespie,M., Matthews,L., Caudy,M., Garapati,P.,
+ Gopinath,G., Jassal,B. et al. (2011) Reactome: a database of
+ reactions, pathways and biological processes. Nucleic Acids Res.,
+ 39, D691–D697.
+26. Demir,E., Cary,M.P., Paley,S., Fukuda,K.,
+ Lemer,C., Vastrik,I.,Wu,G., D’Eustachio,P., Schaefer,C., Luciano,J.
+ et al. (2010) The BioPAX community standard for pathway
+ data sharing. Nature Biotechnol., 28, 935–942.
+27. Alemán Z, GarcĂa-GarcĂa F, Medina I, Dopazo J
+ (2014): A web tool for the design and management of panels of genes
+ for targeted enrichment and massive sequencing for
+ clinical applications. Nucleic Acids Res 42: W83-7.
+28. [Alemán
+ A](http://www.ncbi.nlm.nih.gov/pubmed?term=Alem%C3%A1n%20A%5BAuthor%5D&cauthor=true&cauthor_uid=24803668)>, [Garcia-Garcia
+ F](http://www.ncbi.nlm.nih.gov/pubmed?term=Garcia-Garcia%20F%5BAuthor%5D&cauthor=true&cauthor_uid=24803668)>, [Salavert
+ F](http://www.ncbi.nlm.nih.gov/pubmed?term=Salavert%20F%5BAuthor%5D&cauthor=true&cauthor_uid=24803668)>, [Medina
+ I](http://www.ncbi.nlm.nih.gov/pubmed?term=Medina%20I%5BAuthor%5D&cauthor=true&cauthor_uid=24803668)>, [Dopazo
+ J](http://www.ncbi.nlm.nih.gov/pubmed?term=Dopazo%20J%5BAuthor%5D&cauthor=true&cauthor_uid=24803668)> (2014).
+ A web-based interactive framework to assist in the prioritization of
+ disease candidate genes in whole-exome sequencing studies.
+ [Nucleic
+ Acids Res.](http://www.ncbi.nlm.nih.gov/pubmed/?term=BiERapp "Nucleic acids research.")>42 :W88-93.
+29. Landrum,M.J., Lee,J.M., Riley,G.R., Jang,W.,
+ Rubinstein,W.S., Church,D.M. and Maglott,D.R. (2014) ClinVar: public
+ archive of relationships among sequence variation and
+ human phenotype. Nucleic Acids Res., 42, D980–D985.
+30. Medina I, Salavert F, Sanchez R, de Maria A,
+ Alonso R, Escobar P, Bleda M, Dopazo J: Genome Maps, a new
+ generation genome browser. Nucleic Acids Res 2013, 41:W41-46.
+
+Â
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/omics-master-1/priorization-component-bierapp.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/omics-master-1/priorization-component-bierapp.md
new file mode 100644
index 0000000000000000000000000000000000000000..a6cd22b5866bbbb95035359d3f1ffddf1c4772cf
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/omics-master-1/priorization-component-bierapp.md
@@ -0,0 +1,42 @@
+Priorization component (BiERApp)
+================================
+
+### Access
+
+BiERApp is available at the following address
+:Â <http://omics.it4i.cz/bierapp/>
+
+The address is accessible only
+via [VPN. ](../../accessing-the-cluster/vpn-access.html)
+
+###BiERApp
+
+###This tool is aimed to discover new disease genes or variants by studying affected families or cases and controls. It carries out a filtering process to sequentially remove:Â (i) variants which are not no compatible with the disease because are not expected to have impact on the protein function; (ii) variants that exist at frequencies incompatible with the disease; (iii) variants that do not segregate with the disease. The result is a reduced set of disease gene candidates that should be further validated experimentally.
+
+BiERapp >(28) efficiently helps in the identification of
+causative variants in family and sporadic genetic diseases. The program
+reads lists of predicted variants (nucleotide substitutions and indels)
+in affected individuals or tumor samples and controls. In family
+studies, different modes of inheritance can easily be defined to filter
+out variants that do not segregate with the disease along the family.
+Moreover, BiERapp integrates additional information such as allelic
+frequencies in the general population and the most popular damaging
+scores to further narrow down the number of putative variants in
+successive filtering steps. BiERapp provides an interactive and
+user-friendly interface that implements the filtering strategy used in
+the context of a large-scale genomic project carried out by the Spanish
+Network for Research, in Rare Diseases (CIBERER) and the Medical Genome
+Project. in which more than 800 exomes have been analyzed.
+
+
+
+*Figure 6**. *Web interface to the prioritization tool.* *This
+figure*Â *shows the interface of the web tool for candidate gene
+prioritization with the filters available. The tool includes a genomic
+viewer (Genome Maps >30) that enables the representation of
+the variants in the corresponding genomic coordinates.*
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/openfoam.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/openfoam.md
new file mode 100644
index 0000000000000000000000000000000000000000..f5579ca1e525599353caf270ff971a04d4c23d58
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/openfoam.md
@@ -0,0 +1,261 @@
+OpenFOAM
+========
+
+A free, open source CFD software package
+
+
+
+Introduction**
+----------------
+
+OpenFOAM is a free, open source CFD software package developed
+by [**OpenCFD Ltd**](http://www.openfoam.com/about) at [**ESI
+Group**](http://www.esi-group.com/) and distributed by the [**OpenFOAM
+Foundation **](http://www.openfoam.org/). It has a large user base
+across most areas of engineering and science, from both commercial and
+academic organisations.Â
+
+Homepage: <http://www.openfoam.com/>
+
+###Installed version**
+
+Currently, several version compiled by GCC/ICC compilers in
+single/double precision with several version of openmpi are available on
+Anselm.
+
+For example syntax of available OpenFOAM module is:
+
+< openfoam/2.2.1-icc-openmpi1.6.5-DP >
+
+this means openfoam version >2.2.1 compiled by
+ICC compiler with >openmpi1.6.5 in> double
+precision.
+
+Naming convection of the installed versions is following:
+
+Â Â
+openfoam/<>VERSION>>-<>COMPILER<span>>-<</span><span>openmpiVERSION</span><span>>-<</span><span>PRECISION</span><span>></span>
+
+- ><>VERSION>> - version of
+ openfoam
+- ><>COMPILER> - version of used
+ compiler
+- ><>openmpiVERSION> - version of used
+ openmpi/impi
+- ><>PRECISION> - DP/>SP –
+ double/single precision
+
+###Available OpenFOAM modules**
+
+To check available modules use
+
+ $ module avail
+
+In /opt/modules/modulefiles/engineering you can see installed
+engineering softwares:
+
+ ------------------------------------ /opt/modules/modulefiles/engineering -------------------------------------------------------------
+ ansys/14.5.x              matlab/R2013a-COM                               openfoam/2.2.1-icc-impi4.1.1.036-DP
+ comsol/43b-COMÂ Â Â Â Â Â Â Â Â Â Â Â matlab/R2013a-EDUÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â openfoam/2.2.1-icc-openmpi1.6.5-DP
+ comsol/43b-EDUÂ Â Â Â Â Â Â Â Â Â Â Â openfoam/2.2.1-gcc481-openmpi1.6.5-DPÂ Â Â Â Â Â Â Â Â Â Â paraview/4.0.1-gcc481-bullxmpi1.2.4.1-osmesa10.0
+ lsdyna/7.x.x              openfoam/2.2.1-gcc481-openmpi1.6.5-SP
+
+For information how to use modules please [look
+here](../environment-and-modules.html "Environment and Modules ").
+
+Getting Started**
+-------------------
+
+To create OpenFOAM environment on ANSELM give the commands:
+
+ $ module load openfoam/2.2.1-icc-openmpi1.6.5-DP
+
+ $ source $FOAM_BASHRC
+
+Pleas load correct module with your requirements “compiler - GCC/ICC,
+precision - DP/SP”.
+
+Create a project directory within the $HOME/OpenFOAM directory
+named ><USER>-<OFversion> and create a directory
+named run within it, e.g. by typing:
+
+ $ mkdir -p $FOAM_RUN
+
+Project directory is now available by typing:
+
+ $ cd /home/<USER>/OpenFOAM/<USER>-<OFversion>/run
+
+<OFversion> - for example <2.2.1>
+
+or
+
+ $ cd $FOAM_RUN
+
+Copy the tutorial examples directory in the OpenFOAM distribution to
+the run directory:
+
+ $ cp -r $FOAM_TUTORIALS $FOAM_RUN
+
+Now you can run the first case for example incompressible laminar flow
+in a cavity.
+
+Running Serial Applications**
+-------------------------------
+
+Create a Bash script >test.shÂ
+
+
+ #!/bin/bash
+ module load openfoam/2.2.1-icc-openmpi1.6.5-DP
+ source $FOAM_BASHRC
+
+ # source to run functions
+ . $WM_PROJECT_DIR/bin/tools/RunFunctions
+
+ cd $FOAM_RUN/tutorials/incompressible/icoFoam/cavity
+
+ runApplication blockMesh
+ runApplication icoFoam
+
+
+
+
+
+Job submission
+
+
+ $ qsub -A OPEN-0-0 -q qprod -l select=1:ncpus=16,walltime=03:00:00 test.sh
+
+
+
+ For information about job submission please [look
+here](../resource-allocation-and-job-execution/job-submission-and-execution.html "Job submission").
+
+Running applications in parallel**
+-------------------------------------------------
+
+Run the second case for example external incompressible turbulent
+flow - case - motorBike.
+
+First we must run serial application bockMesh and decomposePar for
+preparation of parallel computation.
+
+Create a Bash scrip test.sh:
+
+
+ #!/bin/bash
+ module load openfoam/2.2.1-icc-openmpi1.6.5-DP
+ source $FOAM_BASHRC
+
+ # source to run functions
+ . $WM_PROJECT_DIR/bin/tools/RunFunctions
+
+ cd $FOAM_RUN/tutorials/incompressible/simpleFoam/motorBike
+
+ runApplication blockMesh
+ runApplication decomposePar
+
+
+
+Job submission
+
+
+ $ qsub -A OPEN-0-0 -q qprod -l select=1:ncpus=16,walltime=03:00:00 test.sh
+
+
+
+This job create simple block mesh and domain decomposition.
+Check your decomposition, and submit parallel computation:
+
+Create a PBS script>
+testParallel.pbs:
+
+
+ #!/bin/bash
+ #PBS -N motorBike
+ #PBS -l select=2:ncpus=16
+ #PBS -l walltime=01:00:00
+ #PBS -q qprod
+ #PBS -A OPEN-0-0
+
+ module load openfoam/2.2.1-icc-openmpi1.6.5-DP
+ source $FOAM_BASHRC
+
+ cd $FOAM_RUN/tutorials/incompressible/simpleFoam/motorBike
+
+ nproc = 32
+
+ mpirun -hostfile ${PBS_NODEFILE} -np $nproc snappyHexMesh -overwrite -parallel | tee snappyHexMesh.log
+
+ mpirun -hostfile ${PBS_NODEFILE} -np $nproc potentialFoam -noFunctionObject-writep -parallel | tee potentialFoam.log
+
+ mpirun -hostfile ${PBS_NODEFILE} -np $nproc simpleFoam -parallel | tee simpleFoam.log
+
+
+
+nproc – number of subdomains
+
+Job submission
+
+
+ $ qsub testParallel.pbs
+
+
+
+Compile your own solver**
+----------------------------------------
+
+Initialize OpenFOAM environment before compiling your solver
+
+
+ $ module load openfoam/2.2.1-icc-openmpi1.6.5-DP
+ $ source $FOAM_BASHRC
+ $ cd $FOAM_RUN/
+
+Create directory applications/solvers in user directory
+
+
+ $ mkdir -p applications/solvers
+ $ cd applications/solvers
+
+
+
+Copy icoFoam solver’s source files
+
+
+ $ cp -r $FOAM_SOLVERS/incompressible/icoFoam/ My_icoFoam
+ $ cd My_icoFoam
+
+Rename icoFoam.C to My_icoFOAM.C
+
+
+ $ mv icoFoam.C My_icoFoam.C
+
+
+
+Edit >*files* file in *Make* directory:
+
+
+ icoFoam.C
+ EXE = $(FOAM_APPBIN)/icoFoam
+
+and change to:
+
+ My_icoFoam.C
+ EXE = $(FOAM_USER_APPBIN)/My_icoFoam
+
+In directory My_icoFoam give the compilation command:
+
+
+ $ wmake
+
+------------------------------------------------------------------------
+
+Â
+
+Â Have a fun with OpenFOAM :)**
+
+Â id="__caret">
+
+Â
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/operating-system.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/operating-system.md
new file mode 100644
index 0000000000000000000000000000000000000000..af15c05074ea33347892db42012d41d0b6b7a7cf
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/operating-system.md
@@ -0,0 +1,13 @@
+Operating System
+================
+
+The operating system, deployed on ANSELM
+
+
+
+The operating system on Anselm is Linux - bullx Linux Server release
+6.3.
+
+bullx Linux is based on Red Hat Enterprise Linux. bullx Linux is a Linux
+distribution provided by Bull and dedicated to HPC applications.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/paraview.md b/converted/docs.it4i.cz/anselm-cluster-documentation/software/paraview.md
new file mode 100644
index 0000000000000000000000000000000000000000..7aafe20e77601fc324681cc958b651ee1b37edcd
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/software/paraview.md
@@ -0,0 +1,121 @@
+ParaView
+========
+
+An open-source, multi-platform data analysis and visualization
+application
+
+
+
+Introduction
+------------
+
+ParaView**Â is an open-source, multi-platform data analysis and
+visualization application. ParaView users can quickly build
+visualizations to analyze their data using qualitative and quantitative
+techniques. The data exploration can be done interactively in 3D or
+programmatically using ParaView's batch processing capabilities.
+
+ParaView was developed to analyze extremely large datasets using
+distributed memory computing resources. It can be run on supercomputers
+to analyze datasets of exascale size as well as on laptops for smaller
+data.
+
+Homepage :Â <http://www.paraview.org/>
+
+Installed version
+-----------------
+
+Currently, version 4.0.1 compiled with GCC 4.8.1 against Bull MPI
+library and OSMesa 10.0 is installed on Anselm.
+
+Usage
+-----
+
+On Anselm, ParaView is to be used in client-server mode. A parallel
+ParaView server is launched on compute nodes by the user, and client is
+launched on your desktop PC to control and view the visualization.
+Download ParaView client application for your OS here
+:Â <http://paraview.org/paraview/resources/software.php>. Important :
+your version must match the version number installed on Anselm** !
+(currently v4.0.1)
+
+### Launching server
+
+To launch the server, you must first allocate compute nodes, for example
+:>Â
+
+ $ qsub -I -q qprod -A OPEN-0-0 -l select=2
+
+to launch an interactive session on 2 nodes. Refer to [Resource
+Allocation and Job
+Execution](../resource-allocation-and-job-execution/introduction.html)
+for details.
+
+After the interactive session is opened, load the ParaView module :
+
+ $ module add paraview
+
+Now launch the parallel server, with number of nodes times 16 processes
+:
+
+ $ mpirun -np 32 pvserver --use-offscreen-rendering
+ Waiting for client...
+ Connection URL: cs://cn77:11111
+ Accepting connection(s): cn77:11111
+
+Â Note the that the server is listening on compute node cn77 in this
+case, we shall use this information later.
+
+### Client connection
+
+Because a direct connection is not allowed to compute nodes on Anselm,
+you must establish a SSH tunnel to connect to the server. Choose a port
+number on your PC to be forwarded to ParaView server, for example 12345.
+If your PC is running Linux, use this command to estabilish a SSH tunnel
+:
+
+ ssh -TN -L 12345:cn77:11111 username@anselm.it4i.cz
+
+replace username with your login and cn77
+with the name of compute node your ParaView server is running on (see
+previous step). If you use PuTTY on Windows, load Anselm connection
+configuration, t>hen go to Connection->
+SSH>->Tunnels to set up the
+port forwarding. Click Remote radio button. Insert 12345 to Source port
+textbox. Insert cn77:11111. Click Add button, then Open. [Read
+more about port
+forwarding.](https://docs.it4i.cz/anselm-cluster-documentation/software/resolveuid/11e53ad0d2fd4c5187537f4baeedff33)
+
+Now launch ParaView client installed on your desktop PC. Select
+File->Connect..., click Add Server. Fill in the following :
+
+Name : Anselm tunnel
+
+Server Type : Client/Server
+
+Host : localhost
+
+Port : 12345
+
+Click Configure, Save, the configuration is now saved for later use. Now
+click Connect to connect to the ParaView server. In your terminal where
+you have interactive session with ParaView server launched, you should
+see :
+
+ Client connected.
+
+You can now use Parallel ParaView.
+
+### Close server
+
+Remember to close the interactive session after you finish working with
+ParaView server, as it will remain launched even after your client is
+disconnected and will continue to consume resources.
+
+GPU support
+-----------
+
+Currently, GPU acceleration is not supported in the server and ParaView
+will not take advantage of accelerated nodes on Anselm. Support for GPU
+acceleration might be added in the future.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/software/virtualization-job-workflow b/converted/docs.it4i.cz/anselm-cluster-documentation/software/virtualization-job-workflow
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diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/storage-1/cesnet-data-storage.md b/converted/docs.it4i.cz/anselm-cluster-documentation/storage-1/cesnet-data-storage.md
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@@ -0,0 +1,128 @@
+CESNET Data Storage
+===================
+
+
+
+Introduction
+------------
+
+Do not use shared filesystems at IT4Innovations as a backup for large
+amount of data or long-term archiving purposes.
+
+The IT4Innovations does not provide storage capacity for data archiving.
+Academic staff and students of research institutions in the Czech
+Republic can use [CESNET Storage
+service](https://du.cesnet.cz/).
+
+The CESNET Storage service can be used for research purposes, mainly by
+academic staff and students of research institutions in the Czech
+Republic.
+
+User of data storage CESNET (DU) association can become organizations or
+an individual person who is either in the current employment
+relationship (employees) or the current study relationship (students) to
+a legal entity (organization) that meets the “Principles for access to
+CESNET Large infrastructure (Access Policy)”.
+
+User may only use data storage CESNET for data transfer and storage
+which are associated with activities in science, research, development,
+the spread of education, culture and prosperity. In detail see
+“Acceptable Use Policy CESNET Large Infrastructure (Acceptable Use
+Policy, AUP)”.
+
+The service is documented at
+<https://du.cesnet.cz/wiki/doku.php/en/start>. For special requirements
+please contact directly CESNET Storage Department via e-mail
+[du-support(at)cesnet.cz](mailto:du-support@cesnet.cz).
+
+The procedure to obtain the CESNET access is quick and trouble-free.
+
+(source
+[https://du.cesnet.cz/](https://du.cesnet.cz/wiki/doku.php/en/start "CESNET Data Storage"))
+
+CESNET storage access
+---------------------
+
+### Understanding Cesnet storage
+
+It is very important to understand the Cesnet storage before uploading
+data. Please read
+<https://du.cesnet.cz/en/navody/home-migrace-plzen/start> first.
+
+Once registered for CESNET Storage, you may [access the
+storage](https://du.cesnet.cz/en/navody/faq/start) in
+number of ways. We recommend the SSHFS and RSYNC methods.
+
+### SSHFS Access
+
+SSHFS: The storage will be mounted like a local hard drive
+
+The SSHFSÂ provides a very convenient way to access the CESNET Storage.
+The storage will be mounted onto a local directory, exposing the vast
+CESNET Storage as if it was a local removable harddrive. Files can be
+than copied in and out in a usual fashion.
+
+First, create the mountpoint
+
+ $ mkdir cesnet
+
+Mount the storage. Note that you can choose among the ssh.du1.cesnet.cz
+(Plzen), ssh.du2.cesnet.cz (Jihlava), ssh.du3.cesnet.cz (Brno)
+Mount tier1_home **(only 5120M !)**:
+
+ $ sshfs username@ssh.du1.cesnet.cz:. cesnet/
+
+For easy future access from Anselm, install your public key
+
+ $ cp .ssh/id_rsa.pub cesnet/.ssh/authorized_keys
+
+Mount tier1_cache_tape for the Storage VO:
+
+ $ sshfs username@ssh.du1.cesnet.cz:/cache_tape/VO_storage/home/username cesnet/
+
+View the archive, copy the files and directories in and out
+
+ $ ls cesnet/
+ $ cp -a mydir cesnet/.
+ $ cp cesnet/myfile .
+
+Once done, please remember to unmount the storage
+
+ $ fusermount -u cesnet
+
+### Rsync access
+
+Rsync provides delta transfer for best performance, can resume
+interrupted transfers
+
+Rsync is a fast and extraordinarily versatile file copying tool. It is
+famous for its delta-transfer algorithm, which reduces the amount of
+data sent over the network by sending only the differences between the
+source files and the existing files in the destination. Rsync is widely
+used for backups and mirroring and as an improved copy command for
+everyday use.
+
+Rsync finds files that need to be transferred using a "quick check"
+algorithm (by default) that looks for files that have changed in size or
+in last-modified time. Any changes in the other preserved attributes
+(as requested by options) are made on the destination file directly when
+the quick check indicates that the file's data does not need to be
+updated.
+
+More about Rsync at
+<https://du.cesnet.cz/en/navody/rsync/start#pro_bezne_uzivatele>
+
+Transfer large files to/from Cesnet storage, assuming membership in the
+Storage VO
+
+ $ rsync --progress datafile username@ssh.du1.cesnet.cz:VO_storage-cache_tape/.
+ $ rsync --progress username@ssh.du1.cesnet.cz:VO_storage-cache_tape/datafile .
+
+Transfer large directories to/from Cesnet storage, assuming membership
+in the Storage VO
+
+ $ rsync --progress -av datafolder username@ssh.du1.cesnet.cz:VO_storage-cache_tape/.
+ $ rsync --progress -av username@ssh.du1.cesnet.cz:VO_storage-cache_tape/datafolder .
+
+Transfer rates of about 28MB/s can be expected.
+
diff --git a/converted/docs.it4i.cz/anselm-cluster-documentation/storage-1/storage.md b/converted/docs.it4i.cz/anselm-cluster-documentation/storage-1/storage.md
new file mode 100644
index 0000000000000000000000000000000000000000..2a58b726d505798696080198c159d55dbc9138f9
--- /dev/null
+++ b/converted/docs.it4i.cz/anselm-cluster-documentation/storage-1/storage.md
@@ -0,0 +1,502 @@
+Storage
+=======
+
+
+
+There are two main shared file systems on Anselm cluster, the
+[HOME](../storage.html#home) and
+[SCRATCH](../storage.html#scratch). All login and compute
+nodes may access same data on shared filesystems. Compute nodes are also
+equipped with local (non-shared) scratch, ramdisk and tmp filesystems.
+
+Archiving
+---------
+
+Please don't use shared filesystems as a backup for large amount of data
+or long-term archiving mean. The academic staff and students of research
+institutions in the Czech Republic can use [CESNET storage
+service](cesnet-data-storage.html), which is available
+via SSHFS.
+
+Shared Filesystems
+------------------
+
+Anselm computer provides two main shared filesystems, the [HOME
+filesystem](../storage.html#home) and the [SCRATCH
+filesystem](../storage.html#scratch). Both HOME and
+SCRATCH filesystems are realized as a parallel Lustre filesystem. Both
+shared file systems are accessible via the Infiniband network. Extended
+ACLs are provided on both Lustre filesystems for the purpose of sharing
+data with other users using fine-grained control.
+
+### Understanding the Lustre Filesystems
+
+(source <http://www.nas.nasa.gov>)
+
+A user file on the Lustre filesystem can be divided into multiple chunks
+(stripes) and stored across a subset of the object storage targets
+(OSTs) (disks). The stripes are distributed among the OSTs in a
+round-robin fashion to ensure load balancing.
+
+When a client (a compute
+node from your job) needs to create
+or access a file, the client queries the metadata server (
+MDS) and the metadata target (
+MDT) for the layout and location of the
+[file's
+stripes](http://www.nas.nasa.gov/hecc/support/kb/Lustre_Basics_224.html#striping).
+Once the file is opened and the client obtains the striping information,
+the MDS is no longer involved in the
+file I/O process. The client interacts directly with the object storage
+servers (OSSes) and OSTs to perform I/O operations such as locking, disk
+allocation, storage, and retrieval.
+
+If multiple clients try to read and write the same part of a file at the
+same time, the Lustre distributed lock manager enforces coherency so
+that all clients see consistent results.
+
+There is default stripe configuration for Anselm Lustre filesystems.
+However, users can set the following stripe parameters for their own
+directories or files to get optimum I/O performance:
+
+1. stripe_size: the size of the chunk in bytes; specify with k, m, or
+ g to use units of KB, MB, or GB, respectively; the size must be an
+ even multiple of 65,536 bytes; default is 1MB for all Anselm Lustre
+ filesystems
+2. stripe_count the number of OSTs to stripe across; default is 1 for
+ Anselm Lustre filesystems one can specify -1 to use all OSTs in
+ the filesystem.
+3. stripe_offset The index of the
+ OST where the first stripe is to be
+ placed; default is -1 which results in random selection; using a
+ non-default value is NOT recommended.
+
+Â
+
+Setting stripe size and stripe count correctly for your needs may
+significantly impact the I/O performance you experience.
+
+Use the lfs getstripe for getting the stripe parameters. Use the lfs
+setstripe command for setting the stripe parameters to get optimal I/O
+performance The correct stripe setting depends on your needs and file
+access patterns.Â
+
+`
+$ lfs getstripe dir|filename
+$ lfs setstripe -s stripe_size -c stripe_count -o stripe_offset dir|filename
+`
+
+Example:
+
+`
+$ lfs getstripe /scratch/username/
+/scratch/username/
+stripe_count: 1 stripe_size: 1048576 stripe_offset: -1
+
+$ lfs setstripe -c -1 /scratch/username/
+$ lfs getstripe /scratch/username/
+/scratch/username/
+stripe_count: 10 stripe_size: 1048576 stripe_offset: -1
+`
+
+In this example, we view current stripe setting of the
+/scratch/username/ directory. The stripe count is changed to all OSTs,
+and verified. All files written to this directory will be striped over
+10 OSTs
+
+Use lfs check OSTs to see the number and status of active OSTs for each
+filesystem on Anselm. Learn more by reading the man page
+
+`
+$ lfs check osts
+$ man lfs
+`
+
+### Hints on Lustre Stripping
+
+Increase the stripe_count for parallel I/O to the same file.
+
+When multiple processes are writing blocks of data to the same file in
+parallel, the I/O performance for large files will improve when the
+stripe_count is set to a larger value. The stripe count sets the number
+of OSTs the file will be written to. By default, the stripe count is set
+to 1. While this default setting provides for efficient access of
+metadata (for example to support the ls -l command), large files should
+use stripe counts of greater than 1. This will increase the aggregate
+I/O bandwidth by using multiple OSTs in parallel instead of just one. A
+rule of thumb is to use a stripe count approximately equal to the number
+of gigabytes in the file.
+
+Another good practice is to make the stripe count be an integral factor
+of the number of processes performing the write in parallel, so that you
+achieve load balance among the OSTs. For example, set the stripe count
+to 16 instead of 15 when you have 64 processes performing the writes.
+
+Using a large stripe size can improve performance when accessing very
+large files
+
+Large stripe size allows each client to have exclusive access to its own
+part of a file. However, it can be counterproductive in some cases if it
+does not match your I/O pattern. The choice of stripe size has no effect
+on a single-stripe file.
+
+Read more on
+<http://wiki.lustre.org/manual/LustreManual20_HTML/ManagingStripingFreeSpace.html>
+
+### Lustre on Anselm
+
+The architecture of Lustre on Anselm is composed of two metadata
+servers (MDS) and four data/object storage servers (OSS). Two object
+storage servers are used for file system HOME and another two object
+storage servers are used for file system SCRATCH.
+
+ Configuration of the storages
+
+- HOME Lustre object storage
+
+
+ - One disk array NetApp E5400
+ - 22 OSTs
+ - 227 2TB NL-SAS 7.2krpm disks
+ - 22 groups of 10 disks in RAID6 (8+2)
+ - 7 hot-spare disks
+
+
+
+- SCRATCH Lustre object storage
+
+
+ - Two disk arrays NetApp E5400
+ - 10 OSTs
+ - 106 2TB NL-SAS 7.2krpm disks
+ - 10 groups of 10 disks in RAID6 (8+2)
+ - 6 hot-spare disks
+
+
+
+- Lustre metadata storage
+
+
+ - One disk array NetApp E2600
+ - 12 300GB SAS 15krpm disks
+ - 2 groups of 5 disks in RAID5
+ - 2 hot-spare disks
+
+
+
+###HOME
+
+The HOME filesystem is mounted in directory /home. Users home
+directories /home/username reside on this filesystem. Accessible
+capacity is 320TB, shared among all users. Individual users are
+restricted by filesystem usage quotas, set to 250GB per user. >If
+250GB should prove as insufficient for particular user, please
+contact [support](https://support.it4i.cz/rt),
+the quota may be lifted upon request.
+
+The HOME filesystem is intended for preparation, evaluation, processing
+and storage of data generated by active Projects.
+
+The HOME filesystem should not be used to archive data of past Projects
+or other unrelated data.
+
+The files on HOME filesystem will not be deleted until end of the [users
+lifecycle](../../get-started-with-it4innovations/obtaining-login-credentials/obtaining-login-credentials.html).
+
+The filesystem is backed up, such that it can be restored in case ofÂ
+catasthropic failure resulting in significant data loss. This backup
+however is not intended to restore old versions of user data or to
+restore (accidentaly) deleted files.Â
+
+The HOME filesystem is realized as Lustre parallel filesystem and is
+available on all login and computational nodes.
+Default stripe size is 1MB, stripe count is 1. There are 22 OSTs
+dedicated for the HOME filesystem.
+
+Setting stripe size and stripe count correctly for your needs may
+significantly impact the I/O performance you experience.
+
+HOME filesystem
+Mountpoint
+/home
+Capacity
+320TB
+Throughput
+2GB/s
+User quota
+250GB
+Default stripe size
+1MB
+Default stripe count
+1
+Number of OSTs
+22
+###SCRATCH
+
+The SCRATCH filesystem is mounted in directory /scratch. Users may
+freely create subdirectories and files on the filesystem. Accessible
+capacity is 146TB, shared among all users. Individual users are
+restricted by filesystem usage quotas, set to 100TB per user. The
+purpose of this quota is to prevent runaway programs from filling the
+entire filesystem and deny service to other users. >If 100TB should
+prove as insufficient for particular user, please contact
+[support](https://support.it4i.cz/rt), the quota may be
+lifted upon request.Â
+
+The Scratch filesystem is intended for temporary scratch data generated
+during the calculation as well as for high performance access to input
+and output files. All I/O intensive jobs must use the SCRATCH filesystem
+as their working directory.
+
+Users are advised to save the necessary data from the SCRATCH filesystem
+to HOME filesystem after the calculations and clean up the scratch
+files.
+
+Files on the SCRATCH filesystem that are **not accessed for more than 90
+days** will be automatically **deleted**.
+
+The SCRATCH filesystem is realized as Lustre parallel filesystem and is
+available from all login and computational nodes.
+Default stripe size is 1MB, stripe count is 1. There are 10 OSTs
+dedicated for the SCRATCH filesystem.
+
+Setting stripe size and stripe count correctly for your needs may
+significantly impact the I/O performance you experience.
+
+SCRATCH filesystem
+Mountpoint
+/scratch
+Capacity
+146TB
+Throughput
+6GB/s
+User quota
+100TB
+Default stripe size
+1MB
+Default stripe count
+1
+Number of OSTs
+10
+### Disk usage and quota commands
+
+User quotas on the file systems can be checked and reviewed using
+following command:
+
+`
+$ lfs quota dir
+`
+
+Example for Lustre HOME directory:
+
+`
+$ lfs quota /home
+Disk quotas for user user001 (uid 1234):
+ Filesystem kbytes quota limit grace files quota limit grace
+ /home 300096 0 250000000 - 2102 0 500000 -
+Disk quotas for group user001 (gid 1234):
+ Filesystem kbytes quota limit grace files quota limit grace
+ /home 300096 0 0 - 2102 0 0 -
+`
+
+In this example, we view current quota size limit of 250GB and 300MB
+currently used by user001.
+
+Example for Lustre SCRATCH directory:
+
+`
+$ lfs quota /scratch
+Disk quotas for user user001 (uid 1234):
+ Filesystem kbytes quota limit grace files quota limit grace
+  /scratch    8    0 100000000000    -    3    0    0    -
+Disk quotas for group user001 (gid 1234):
+ Filesystem kbytes quota limit grace files quota limit grace
+ /scratch    8    0    0    -    3    0    0    -
+`
+
+In this example, we view current quota size limit of 100TB and 8KB
+currently used by user001.
+
+Â
+
+To have a better understanding of where the space is exactly used, you
+can use following command to find out.
+
+`
+$ du -hs dir
+`
+
+Example for your HOME directory:
+
+`
+$ cd /home
+$ du -hs * .[a-zA-z0-9]* | grep -E "[0-9]*G|[0-9]*M" | sort -hr
+258M cuda-samples
+15M .cache
+13M .mozilla
+5,5M .eclipse
+2,7M .idb_13.0_linux_intel64_app
+`
+
+This will list all directories which are having MegaBytes or GigaBytes
+of consumed space in your actual (in this example HOME) directory. List
+is sorted in descending order from largest to smallest
+files/directories.
+
+To have a better understanding of previous commands, you can read
+manpages.
+
+`
+$ man lfs
+`
+
+`
+$ man du
+`
+
+### Extended ACLs
+
+Extended ACLs provide another security mechanism beside the standard
+POSIX ACLs which are defined by three entries (for
+owner/group/others). Extended ACLs have more than the three basic
+entries. In addition, they also contain a mask entry and may contain any
+number of named user and named group entries.
+
+ACLs on a Lustre file system work exactly like ACLs on any Linux file
+system. They are manipulated with the standard tools in the standard
+manner. Below, we create a directory and allow a specific user access.
+
+`
+[vop999@login1.anselm ~]$ umask 027
+[vop999@login1.anselm ~]$ mkdir test
+[vop999@login1.anselm ~]$ ls -ld test
+drwxr-x--- 2 vop999 vop999 4096 Nov 5 14:17 test
+[vop999@login1.anselm ~]$ getfacl test
+# file: test
+# owner: vop999
+# group: vop999
+user::rwx
+group::r-x
+other::---
+
+[vop999@login1.anselm ~]$ setfacl -m user:johnsm:rwx test
+[vop999@login1.anselm ~]$ ls -ld test
+drwxrwx---+ 2 vop999 vop999 4096 Nov 5 14:17 test
+[vop999@login1.anselm ~]$ getfacl test
+# file: test
+# owner: vop999
+# group: vop999
+user::rwx
+user:johnsm:rwx
+group::r-x
+mask::rwx
+other::---
+`
+
+Default ACL mechanism can be used to replace setuid/setgid permissions
+on directories. Setting a default ACL on a directory (-d flag to
+setfacl) will cause the ACL permissions to be inherited by any newly
+created file or subdirectory within the directory. Refer to this page
+for more information on Linux ACL:
+
+[http://www.vanemery.com/Linux/ACL/POSIX_ACL_on_Linux.html ](http://www.vanemery.com/Linux/ACL/POSIX_ACL_on_Linux.html)
+
+Local Filesystems
+-----------------
+
+### Local Scratch
+
+Every computational node is equipped with 330GB local scratch disk.
+
+Use local scratch in case you need to access large amount of small files
+during your calculation.
+
+The local scratch disk is mounted as /lscratch and is accessible to
+user at /lscratch/$PBS_JOBID directory.
+
+The local scratch filesystem is intended for temporary scratch data
+generated during the calculation as well as for high performance access
+to input and output files. All I/O intensive jobs that access large
+number of small files within the calculation must use the local scratch
+filesystem as their working directory. This is required for performance
+reasons, as frequent access to number of small files may overload the
+metadata servers (MDS) of the Lustre filesystem.
+
+The local scratch directory /lscratch/$PBS_JOBID will be deleted
+immediately after the calculation end. Users should take care to save
+the output data from within the jobscript.
+
+local SCRATCH filesystem
+Mountpoint
+/lscratch
+Accesspoint
+/lscratch/$PBS_JOBID
+Capacity
+330GB
+Throughput
+100MB/s
+User quota
+none
+### RAM disk
+
+Every computational node is equipped with filesystem realized in memory,
+so called RAM disk.
+
+Use RAM disk in case you need really fast access to your data of limited
+size during your calculation.
+Be very careful, use of RAM disk filesystem is at the expense of
+operational memory.
+
+The local RAM disk is mounted as /ramdisk and is accessible to user
+at /ramdisk/$PBS_JOBID directory.
+
+The local RAM disk filesystem is intended for temporary scratch data
+generated during the calculation as well as for high performance access
+to input and output files. Size of RAM disk filesystem is limited. Be
+very careful, use of RAM disk filesystem is at the expense of
+operational memory. It is not recommended to allocate large amount of
+memory and use large amount of data in RAM disk filesystem at the same
+time.
+
+The local RAM disk directory /ramdisk/$PBS_JOBID will be deleted
+immediately after the calculation end. Users should take care to save
+the output data from within the jobscript.
+
+RAM disk
+Mountpoint
+ /ramdisk
+Accesspoint
+ /ramdisk/$PBS_JOBID
+Capacity
+60GB at compute nodes without accelerator
+
+90GB at compute nodes with accelerator
+
+500GB at fat nodes
+
+Throughput
+over 1.5 GB/s write, over 5 GB/s read, single thread
+over 10 GB/s write, over 50 GB/s read, 16 threads
+
+User quota
+none
+### tmp
+
+Each node is equipped with local /tmp directory of few GB capacity. The
+/tmp directory should be used to work with small temporary files. Old
+files in /tmp directory are automatically purged.
+
+Summary
+
+----------
+
+ Mountpoint Usage Protocol Net Capacity Throughput Limitations Access Services
+ ------------------------------------ |---|---|----------------- ---------- ---------------- ------------ ------------- ---------- |**Version**|**Module**|------
+ /home home directory Lustre 320 TiB 2 GB/s Quota 250GB Compute and login nodes backed up
+ /scratch cluster shared jobs' data Lustre 146 TiB 6 GB/s Quota 100TB Compute and login nodes files older 90 days removed
+ /lscratch node local jobs' data local 330 GB 100 MB/s none Compute nodes purged after job ends
+ /ramdisk node local jobs' data local 60, 90, 500 GB 5-50 GB/s none Compute nodes purged after job ends
+ /tmp local temporary files local 9.5 GB 100 MB/s none Compute and login nodes auto purged
+
+Â
+
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@@ -0,0 +1,44 @@
+Cygwin and X11 forwarding
+=========================
+
+### If no able to forward X11 using PuTTY to CygwinX
+
+`
+[usename@login1.anselm ~]$ gnome-session &
+[1] 23691
+[usename@login1.anselm ~]$ PuTTY X11 proxy: unable to connect to forwarded X server: Network error: Connection refused
+PuTTY X11 proxy: unable to connect to forwarded X server: Network error: Connection refused
+
+ (gnome-session:23691): WARNING **: Cannot open display:**
+`
+
+ Â
+
+1. Locate and modify
+ Cygwin shortcut that
+ uses
+ Â [startxwin](http://x.cygwin.com/docs/man1/startxwin.1.html)
+ locate
+ C:cygwin64binXWin.exe
+
+
+ change it
+ to
+ C:*cygwin64binXWin.exe -listen tcp*
+
+ 
+
+
+
+2.
+ Check Putty settings:
+ Enable X11
+ forwarding
+
+
+
+ 
+
+
+Â
+
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@@ -0,0 +1,29 @@
+Graphical User Interface
+========================
+
+
+
+X Window System
+---------------
+
+The X Window system is a principal way to get GUI access to the
+clusters.
+
+Read more about configuring [**X Window
+System**](x-window-system/x-window-and-vnc.html).
+
+VNC
+---
+
+The **Virtual Network Computing** (**VNC**) is a graphical
+[desktop
+sharing](http://en.wikipedia.org/wiki/Desktop_sharing "Desktop sharing")
+system that uses the [Remote Frame Buffer
+protocol
+(RFB)](http://en.wikipedia.org/wiki/RFB_protocol "RFB protocol")
+to remotely control another
+[computer](http://en.wikipedia.org/wiki/Computer "Computer").
+
+Read more about configuring
+**[VNC](../../../salomon/accessing-the-cluster/graphical-user-interface/vnc.html)**.
+
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@@ -0,0 +1,269 @@
+VNC
+===
+
+
+
+The **Virtual Network Computing** (**VNC**) is a graphical [desktop
+sharing](http://en.wikipedia.org/wiki/Desktop_sharing "Desktop sharing")
+system that uses the [Remote Frame Buffer protocol
+(RFB)](http://en.wikipedia.org/wiki/RFB_protocol "RFB protocol") to
+remotely control another
+[computer](http://en.wikipedia.org/wiki/Computer "Computer"). It
+transmits the
+[keyboard](http://en.wikipedia.org/wiki/Computer_keyboard "Computer keyboard")
+and
+[mouse](http://en.wikipedia.org/wiki/Computer_mouse "Computer mouse")
+events from one computer to another, relaying the graphical
+[screen](http://en.wikipedia.org/wiki/Computer_screen "Computer screen")
+updates back in the other direction, over a
+[network](http://en.wikipedia.org/wiki/Computer_network "Computer network").(http://en.wikipedia.org/wiki/Virtual_Network_Computing#cite_note-1)
+
+The recommended clients are
+[TightVNC](http://www.tightvnc.com) or
+[TigerVNC](http://sourceforge.net/apps/mediawiki/tigervnc/index.php?title=Main_Page)
+(free, open source, available for almost any platform).
+
+Create VNC password
+-------------------
+
+Local VNC password should be set before the first login. Do use a strong
+password.
+
+`
+[username@login2 ~]$ vncpasswd
+Password:
+Verify:
+`
+
+Start vncserver
+---------------
+
+To access VNC a local vncserver must be started first and also a tunnel
+using SSH port forwarding must be established.
+[See below](vnc.html#linux-example-of-creating-a-tunnel)
+for the details on SSH tunnels. In this example we use port 61.
+
+You can find ports which are already occupied. Here you can see that
+ports " /usr/bin/Xvnc :79" and "
+/usr/bin/Xvnc :60" are occupied.
+
+`
+[username@login2 ~]$ ps aux | grep Xvnc
+username   5971 0.0 0.0 201072 92564 ?       SN  Sep22  4:19 /usr/bin/Xvnc :79 -desktop login2:79 (username) -auth /home/gre196/.Xauthority -geometry 1024x768 -rfbwait 30000 -rfbauth /home/username/.vnc/passwd -rfbport 5979 -fp catalogue:/etc/X11/fontpath.d -pn
+username   10296 0.0 0.0 131772 21076 pts/29  SN  13:01  0:01 /usr/bin/Xvnc :60 -desktop login2:61 (username) -auth /home/username/.Xauthority -geometry 1600x900 -depth 16 -rfbwait 30000 -rfbauth /home/jir13/.vnc/passwd -rfbport 5960 -fp catalogue:/etc/X11/fontpath.d -pn
+.....
+`
+
+Choose free port e.g. 61 and start your VNC server:
+
+`
+[username@login2 ~]$ vncserver :61 -geometry 1600x900 -depth 16
+
+New 'login2:1 (username)' desktop is login2:1
+
+Starting applications specified in /home/username/.vnc/xstartup
+Log file is /home/username/.vnc/login2:1.log
+`
+
+Check if VNC server is started on the port (in this example 61):
+
+`
+[username@login2 .vnc]$ vncserver -list
+
+TigerVNC server sessions:
+
+X DISPLAY #Â Â Â Â PROCESS ID
+:61Â Â Â Â Â Â Â Â Â Â Â Â Â 18437
+`
+
+Another command:
+
+`
+[username@login2 .vnc]$ Â ps aux | grep Xvnc
+
+username   10296 0.0 0.0 131772 21076 pts/29  SN  13:01  0:01 /usr/bin/Xvnc :61 -desktop login2:61 (username) -auth /home/jir13/.Xauthority -geometry 1600x900 -depth 16 -rfbwait 30000 -rfbauth /home/username/.vnc/passwd -rfbport 5961 -fp catalogue:/etc/X11/fontpath.d -pn
+`
+
+To access the VNC server you have to create a tunnel between the login
+node using TCP **port 5961** and your machine using a free TCP port (for
+simplicity the very same, in this case).
+
+The tunnel must point to the same login node where you launched the VNC
+server, eg. login2. If you use just cluster-name.it4i.cz, the tunnel
+might point to a different node due to DNS round robin.
+
+###Linux/Mac OS example of creating a tunnel
+
+At your machine, create the tunnel:
+
+`
+local $Â ssh -TN -f username@login2.cluster-name.it4i.cz -L 5961:localhost:5961
+`
+
+Issue the following command to check the tunnel is established (please
+note the PID 2022 in the last column, you'll need it for closing the
+tunnel):
+
+`
+local $ netstat -natp | grep 5961
+(Not all processes could be identified, non-owned process info
+Â will not be shown, you would have to be root to see it all.)
+tcp       0     0 127.0.0.1:5961         0.0.0.0:*              LISTEN     2022/ssh      Â
+tcp6Â Â Â Â Â Â 0Â Â Â Â Â 0 ::1:5961Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â :::*Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â LISTENÂ Â Â Â Â 2022/ssh
+`
+
+Or on Mac OS use this command:
+
+`
+local-mac $ lsof -n -i4TCP:5961 | grep LISTEN
+ssh 75890 sta545 7u IPv4 0xfb062b5c15a56a3b 0t0 TCP 127.0.0.1:5961 (LISTEN)
+`
+
+Connect with the VNC client:
+
+`
+local $ vncviewer 127.0.0.1:5961
+`
+
+In this example, we connect to VNC server on port 5961, via the ssh
+tunnel. The connection is encrypted and secured. The VNC server
+listening on port 5961 provides screen of 1600x900 pixels.
+
+You have to destroy the SSH tunnel which is still running at the
+background after you finish the work. Use the following command (PID
+2022 in this case, see the netstat command above):
+
+`
+kill 2022
+`
+
+### Windows example of creating a tunnel
+
+Use PuTTY to log in on cluster.
+
+Start vncserver using command vncserver described above.
+
+**Search for the localhost and port number (in this case
+127.0.0.1:5961).**
+
+`
+[username@login2 .vnc]$ netstat -tanp | grep Xvnc
+(Not all processes could be identified, non-owned process info
+Â will not be shown, you would have to be root to see it all.)
+tcp       0     0 127.0.0.1:5961             0.0.0.0:*                  LISTEN     24031/Xvnc
+`
+
+On the PuTTY Configuration screen go to Connection->SSH->Tunnels
+to set up the tunnel.
+
+Fill the Source port and Destination fields. **Do not forget to click
+the Add button**.
+
+
+
+Run the VNC client of your choice, select VNC server 127.0.0.1, port
+5961 and connect using VNC password.
+
+### Example of starting TigerVNC viewer
+
+
+
+In this example, we connect to VNC server on port 5961, via the ssh
+tunnel, using TigerVNC viewer. The connection is encrypted and secured.
+The VNC server listening on port 5961 provides screen of 1600x900
+pixels.
+
+### Example of starting TightVNC Viewer
+
+Use your VNC password to log using TightVNC Viewer and start a Gnome
+Session on the login node.
+
+
+
+Gnome session
+-------------
+
+You should see after the successful login.
+
+
+
+###Disable your Gnome session screensaver
+
+Open Screensaver preferences dialog:
+
+
+
+Uncheck both options below the slider:
+
+
+
+### Kill screensaver if locked screen
+
+If the screen gets locked you have to kill the screensaver. Do not to
+forget to disable the screensaver then.
+
+`
+[username@login2 .vnc]$ ps aux | grep screen
+username    1503 0.0 0.0 103244  892 pts/4   S+  14:37  0:00 grep screen
+username    24316 0.0 0.0 270564 3528 ?       Ss  14:12  0:00 gnome-screensaver
+
+[username@login2 .vnc]$ kill 24316
+`
+
+### Kill vncserver after finished work
+
+You should kill your VNC server using command:
+
+`
+[username@login2 .vnc]$ vncserver -kill :61
+Killing Xvnc process ID 7074
+Xvnc process ID 7074 already killed
+`
+
+Or this way:
+
+`
+[username@login2 .vnc]$Â pkill vnc
+`
+
+GUI applications on compute nodes over VNC
+------------------------------------------
+
+The very [same methods as described
+above](https://docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-and-vnc#gui-applications-on-compute-nodes),
+may be used to run the GUI applications on compute nodes. However, for
+maximum performance, proceed following these steps:
+
+Open a Terminal (Applications -> System Tools -> Terminal). Run
+all the next commands in the terminal.
+
+
+
+Allow incoming X11 graphics from the compute nodes at the login node:
+
+`
+$ xhost +
+`
+
+Get an interactive session on a compute node (for more detailed info
+[look
+here](../../../../anselm-cluster-documentation/resource-allocation-and-job-execution/job-submission-and-execution.html)).
+Use the **-v DISPLAY** option to propagate the DISPLAY on the compute
+node. In this example, we want a complete node (24 cores in this
+example) from the production queue:
+
+`
+$ qsub -I -v DISPLAY=$(uname -n):$(echo $DISPLAY | cut -d ':' -f 2) -A PROJECT_ID -q qprod -l select=1:ncpus=24
+`
+
+Test that the DISPLAY redirection into your VNC session works, by
+running a X11 application (e. g. XTerm) on the assigned compute node:
+
+`
+$ xterm
+`
+
+Example described above:
+
+
+
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diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system.md b/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system.md
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@@ -0,0 +1,178 @@
+X Window System
+===============
+
+
+
+The X Window system is a principal way to get GUI access to the
+clusters. The **X Window System** (commonly known as **X11**, based on
+its current major version being 11, or shortened to simply **X**, and
+sometimes informally **X-Windows**) is a computer software system and
+network
+[protocol](http://en.wikipedia.org/wiki/Protocol_%28computing%29 "Protocol (computing)")
+that provides a basis for [graphical user
+interfaces](http://en.wikipedia.org/wiki/Graphical_user_interface "Graphical user interface")
+(GUIs) and rich input device capability for [networked
+computers](http://en.wikipedia.org/wiki/Computer_network "Computer network").
+
+The X display forwarding must be activated and the X server running on
+client side
+
+### X display
+
+In order to display graphical user interface GUI of various software
+tools, you need to enable the X display forwarding. On Linux and Mac,
+log in using the -X option tho ssh client:
+
+`
+ local $ ssh -X username@cluster-name.it4i.cz
+`
+
+### X Display Forwarding on Windows
+
+On Windows use the PuTTY client to enable X11 forwarding. Â In PuTTY
+menu, go to Connection->SSH->X11, mark the Enable X11 forwarding
+checkbox before logging in. Then log in as usual.
+
+To verify the forwarding, type
+
+`
+$ echo $DISPLAY
+`
+
+if you receive something like
+
+`
+localhost:10.0
+`
+
+then the X11 forwarding is enabled.
+
+### X Server
+
+In order to display graphical user interface GUI of various software
+tools, you need running X server on your desktop computer. For Linux
+users, no action is required as the X server is the default GUI
+environment on most Linux distributions. Mac and Windows users need to
+install and run the X server on their workstations.
+
+### X Server on OS X
+
+Mac OS users need to install [XQuartz
+server](http://xquartz.macosforge.org/landing/).
+
+### X Server on Windows
+
+There are variety of X servers available for Windows environment. The
+commercial Xwin32 is very stable and rich featured. The Cygwin
+environment provides fully featured open-source XWin X server. For
+simplicity, we recommend open-source X server by the [Xming
+project](http://sourceforge.net/projects/xming/). For
+stability and full features we recommend the
+[XWin](http://x.cygwin.com/) X server by Cygwin
+
+ |How to use Xwin |How to use Xming |
+ | --- | --- |
+ |[Install Cygwin](http://x.cygwin.com/)Find and execute XWin.exeto start the X server on Windows desktop computer.[If no able to forward X11 using PuTTY to CygwinX](x-window-system/cygwin-and-x11-forwarding.html)\ |<p>Use Xlaunch to configure the Xming.<p>Run Xmingto start the X server on Windows desktop computer.\ |
+
+Read more on
+[http://www.math.umn.edu/systems_guide/putty_xwin32.html](http://www.math.umn.edu/systems_guide/putty_xwin32.shtml)
+
+### Running GUI Enabled Applications
+
+Make sure that X forwarding is activated and the X server is running.
+
+Then launch the application as usual. Use the & to run the application
+in background.
+
+`
+$ module load intel (idb and gvim not installed yet)
+$ gvim &
+`
+
+`
+$ xterm
+`
+
+In this example, we activate the intel programing environment tools,
+then start the graphical gvim editor.
+
+### GUI Applications on Compute Nodes
+
+Allocate the compute nodes using -X option on the qsub command
+
+`
+$ qsub -q qexp -l select=2:ncpus=24 -X -I
+`
+
+In this example, we allocate 2 nodes via qexp queue, interactively. We
+request X11 forwarding with the -X option. It will be possible to run
+the GUI enabled applications directly on the first compute node.
+
+**Better performance** is obtained by logging on the allocated compute
+node via ssh, using the -X option.
+
+`
+$ ssh -X r24u35n680
+`
+
+In this example, we log in on the r24u35n680 compute node, with the X11
+forwarding enabled.
+
+HTML commented section #1 (no GUI on Compute nodes - Xvfb)
+
+### The Gnome GUI Environment
+
+The Gnome 2.28 GUI environment is available on the clusters. We
+recommend to use separate X server window for displaying the Gnome
+environment.
+
+### Gnome on Linux and OS X
+
+To run the remote Gnome session in a window on Linux/OS X computer, you
+need to install Xephyr. Ubuntu package is
+xserver-xephyr, on OS X it is part of
+[XQuartz](http://xquartz.macosforge.org/landing/).
+First, launch Xephyr on local machine:
+
+`
+local $ Xephyr -ac -screen 1024x768 -br -reset -terminate :1 &
+`
+
+This will open a new X window with size 1024x768 at DISPLAY :1. Next,
+ssh to the cluster with DISPLAY environment variable set and launch
+ gnome-session
+
+ local $ DISPLAY=:1.0 ssh -XC yourname@cluster-name.it4i.cz -i ~/.ssh/path_to_your_key
+ ... cluster-name MOTD...
+ yourname@login1.cluster-namen.it4i.cz $Â gnome-session &
+
+On older systems where Xephyr is not available, you may also try Xnest
+instead of Xephyr. Another option is to launch a new X server in a
+separate console, via:
+
+`
+xinit /usr/bin/ssh -XT -i .ssh/path_to_your_key yourname@cluster-namen.it4i.cz gnome-session -- :1 vt12
+`
+
+However this method does not seem to work with recent Linux
+distributions and you will need to manually source
+/etc/profile to properly set environment
+variables for PBS.
+
+### Gnome on Windows
+
+Use Xlaunch to start the Xming server or run the XWin.exe. Select the
+''One window" mode.
+
+Log in to the cluster, using PuTTY. On the cluster, run the
+gnome-session command.
+
+`
+$ gnome-session &
+`
+
+In this way, we run remote gnome session on the cluster, displaying it
+in the local X server
+
+Use System->Log Out to close the gnome-session
+
diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/introduction.md b/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/introduction.md
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@@ -0,0 +1,22 @@
+Accessing the Clusters
+======================
+
+The IT4Innovations clusters are accessed by SSH protocol via login
+nodes.
+
+Read more on [Accessing the Salomon
+Cluste](../salomon/accessing-the-cluster.html)r or
+[Accessing the Anselm
+Cluster](../anselm-cluster-documentation/accessing-the-cluster.html)
+pages.
+
+### PuTTY
+
+On **Windows**, use [PuTTY ssh
+client](accessing-the-clusters/shell-access-and-data-transfer/putty/putty.html).
+
+### SSH keys
+
+Read more about [SSH keys
+management](accessing-the-clusters/shell-access-and-data-transfer/ssh-keys.html).
+
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@@ -0,0 +1,21 @@
+Accessing the Clusters
+======================
+
+The IT4Innovations clusters are accessed by SSH protocol via login
+nodes.
+
+Read more on [Accessing the Salomon
+Cluste](../../../salomon/accessing-the-cluster.html)r or
+[Accessing the Anselm
+Cluster](../../../anselm-cluster-documentation/accessing-the-cluster.html)
+pages.
+
+### PuTTY
+
+On **Windows**, use [PuTTY ssh
+client](putty/putty.html).
+
+### SSH keys
+
+Read more about [SSH keys management](ssh-keys.html).
+
diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/pageant.md b/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/pageant.md
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@@ -0,0 +1,19 @@
+Pageant SSH agent
+=================
+
+
+
+Pageant holds your private key in memory without needing to retype a
+passphrase on every login.
+
+- Run Pageant.
+- On Pageant Key List press *Add key* and select your private
+ key (id_rsa.ppk).
+- Enter your passphrase.
+- Now you have your private key in memory without needing to retype a
+ passphrase on every login.
+
+ 
+
+Â
+
diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/putty.md b/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/putty.md
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+++ b/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/putty.md
@@ -0,0 +1,89 @@
+PuTTY
+=====
+
+
+
+PuTTY - before we start SSH connection
+---------------------------------------------------------------------------------
+
+### Windows PuTTY Installer
+
+We recommned you to download "**A Windows installer for everything
+except PuTTYtel**" with **Pageant*** (SSH authentication agent) and
+**PuTTYgen** (PuTTY key generator) which is available
+[here](http://www.chiark.greenend.org.uk/~sgtatham/putty/download.html).
+
+ After installation you can proceed directly
+to private keys authentication using
+["Putty"](putty.html#putty).
+"Change Password for Existing Private Key" is optional.
+"Generate a New Public/Private key (`id_rsa/id_rsa.ppk` ): `600 (-rw-------)` pair" is intended for users without
+Public/Private key (`id_rsa/id_rsa.ppk` ): `600 (-rw-------)` in the initial email containing login credentials.
+"Pageant" is optional.
+
+### PuTTYgen
+
+PuTTYgen is the PuTTY key generator. Read more how to load in an
+existing private key and change your passphrase or generate a new
+public/private key pair using [PuTTYgen](puttygen.html)
+if needed.
+
+### Pageant SSH agent
+
+[Pageant](pageant.html) holds your private key in memory
+without needing to retype a passphrase on every login. We recommend its
+usage.
+
+PuTTY - how to connect to the IT4Innovations cluster
+--------------------------------------------------------
+
+- Run PuTTY
+- Enter Host name and Save session fields with [Login
+ address](../../../../salomon/accessing-the-cluster/shell-and-data-access/shell-and-data-access.html)
+ and browse Connection - > SSH -> Auth menu.
+ The *Host Name* input may be in the format
+ **"username@clustername.it4i.cz"** so you don't have to type your
+ login each time.
+ In this example we will connect to the Salomon cluster using
+ Â **"salomon.it4i.cz"**.
+
+ 
+
+Â
+
+- Category -> Connection - > SSH -> Auth:
+ Select Attempt authentication using Pageant.
+ Select Allow agent forwarding.
+ Browse and select your [private
+ key](../ssh-keys.html) file.
+
+ 
+
+- Return to Session page and Save selected configuration with *Save*
+ button.
+
+ 
+
+- Now you can log in using *Open* button.
+
+ 
+
+- Enter your username if the *Host Name* input is not in the format
+ "username@salomon.it4i.cz".
+
+- Enter passphrase for selected [private
+ key](../ssh-keys.html) file if Pageant **SSH
+ authentication agent is not used.**
+
+
+Another PuTTY Settings
+----------------------
+
+- Category -> Windows -> Translation -> Remote character set
+ and select **UTF-8**.
+
+- Category -> Terminal -> Features and select **Disable
+ application keypad mode** (enable numpad)
+- Save your configuration on Session page in to Default Settings with
+ *Save* button .
+
diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/puttygen.md b/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/puttygen.md
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@@ -0,0 +1,70 @@
+PuTTY key generator
+===================
+
+
+
+PuTTYgen is the PuTTY key generator. You can load in an existing private
+key and change your passphrase or generate a new public/private key
+pair.
+
+### Change Password for Existing Private Key
+
+You can change the password of your SSH key with "PuTTY Key Generator".
+Make sure to backup the key.
+
+- Load your [private key](../ssh-keys.html) file with
+ *Load* button.
+- Enter your current passphrase.
+- Change key passphrase.
+- Confirm key passphrase.
+- Save your private key with *Save private key* button.
+
+ 
+
+Â
+
+### Generate a New Public/Private key (`id_rsa/id_rsa.ppk` ): `600 (-rw-------)` pair
+
+You can generate an additional public/private key pair and insert public
+key into authorized_keys file for authentication with your own private
+key.
+
+- Start with *Generate* button.
+
+ 
+
+- Generate some randomness.
+
+ 
+
+- Wait.
+
+ 
+
+- Enter a *comment* for your key using formatÂ
+ 'username@organization.example.com'.
+ Enter key passphrase.
+ Confirm key passphrase.
+ Save your new private key `in "*.ppk" `format with *Save private
+ key* button.
+
+ 
+
+- Save the public key with *Save public key* button.
+ You can copy public key out of the â€Public key for pasting into
+ authorized_keys file’ box.
+
+ 
+
+- Export private key in OpenSSH format "id_rsa" using Conversion
+ -> Export OpenSSH key
+
+ 
+
+- Now you can insert additional public key into authorized_keys file
+ for authentication with your own private key.
+ You must log in using ssh key received after registration. Then
+ proceed to [How to add your own
+ key](../ssh-keys.html).
+
+
diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/ssh-keys.md b/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/ssh-keys.md
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@@ -0,0 +1,146 @@
+SSH keys
+========
+
+
+
+ Key management
+-------------------------------------------------------------------
+
+After logging in, you can see .ssh/ directory with SSH keys and
+authorized_keys file:
+
+ $ cd /home/username/
+ $ ls -la .ssh/
+ total 24
+ drwx------ 2 username username 4096 May 13 15:12 .
+ drwxr-x---22 username username 4096 May 13 07:22 ..
+ -rw-r--r-- 1 username username 392 May 21 2014 authorized_keys
+ -rw------- 1 username username 1675 May 21Â 2014 id_rsa
+ -rw------- 1 username username 1460 May 21Â 2014 id_rsa.ppk
+ -rw-r--r-- 1 username username 392 May 21 2014 id_rsa.pub
+
+ Please note that private keys in
+.ssh directory are without passphrase and allow you to connect within
+the cluster.
+
+### Access privileges on .ssh folder
+
+- `.ssh` Â directory: 700 (drwx------)
+
+ Â directory:
+ 700 (drwx------)
+-
+ Authorized_keys, known_hosts and public key (`.pub` file): `644 (-rw-r--r--)`Â
+
+
+ known_hosts and
+ public keyÂ
+ (`.pub`
+
+ Â file):Â
+
+ `644 (-rw-r--r--)`
+-
+ ``
+
+ Private key (`id_rsa/id_rsa.ppk` ): `600 (-rw-------)`
+ (`id_rsa/id_rsa.ppk`
+ ):
+ `600 (-rw-------)`
+
+
+
+ cd /home/username/
+ chmod 700 .ssh/
+ chmod 644 .ssh/authorized_keys
+ chmod 644 .ssh/id_rsa.pub
+ chmod 644 .ssh/known_hosts
+ chmod 600 .ssh/id_rsa
+ chmod 600Â .ssh/id_rsa.ppk
+
+Private key (`id_rsa/id_rsa.ppk` ): `600 (-rw-------)`
+-----------
+
+The path to a private key is usually /home/username/.ssh/
+
+Private key (`id_rsa/id_rsa.ppk` ): `600 (-rw-------)` file in "id_rsa" or `"*.ppk" `format is used to
+authenticate with the servers.
+Private key (`id_rsa/id_rsa.ppk` ): `600 (-rw-------)` is present locally
+on local side and used for example in SSH agent [Pageant (for Windows
+users)](putty/PageantV.png). The private key should
+always be kept in a safe place.
+
+ An example of private key
+format:
+
+ -----BEGIN RSA PRIVATE KEY-----
+ MIIEpAIBAAKCAQEAqbo7jokygnBpG2wYa5NB45ns6+UKTNLMLHF0BO3zmRtKEElE
+ aGqXfbYwvXlcuRb2d9/Y5dVpCZHV0kbY3NhtVOcEIe+1ROaiU9BEsUAhMNEvgiLV
+ gSql4QvRO4BWPlM8+WAWXDp3oeoBh8glXyuh9teb8yq98fv1r1peYGRrW3/s4V+q
+ O1SQ0XY2T7rWCYRLIP6rTMXArTI35v3WU513mn7nm1fJ7oN0QgVH5b0W9V1Kyc4l
+ 9vILHeMXxvz+i/5jTEfLOJpiRGYZYcaYrE4dIiHPl3IlbV7hlkK23Xb1US8QJr5G
+ ADxp1VTkHjY+mKagEfxl1hQIb42JLHhKMEGqNQIDAQABAoIBAQCkypPuxZjL+vai
+ UGa5dAWiRZ46P2yrwHPKpvEdpCdDPbLAc1K/CtdBkHZsUPxNHVV6eFWweW99giIY
+ Av+mFWC58X8asBHQ7xkmxW0cqAZRzpkRAl9IBS9/fKjO28Fgy/p+suOi8oWbKIgJ
+ 3LMkX0nnT9oz1AkOfTNC6Tv+3SE7eTj1RPcMjur4W1Cd1N3EljLszdVk4tLxlXBS
+ yl9NzVnJJbJR4t01l45VfFECgYEAno1WJSB/SwdZvS9GkfhvmZd3r4vyV9Bmo3dn
+ XZAh8HRW13imOnpklDR4FRe98D9A7V3yh9h60Co4oAUd6N+Oc68/qnv/8O9efA+M
+ /neI9ANYFo8F0+yFCp4Duj7zPV3aWlN/pd8TNzLqecqh10uZNMy8rAjCxybeZjWd
+ DyhgywXhAoGBAN3BCazNefYpLbpBQzwes+f2oStvwOYKDqySWsYVXeVgUI+OWTVZ
+ eZ26Y86E8MQO+q0TIxpwou+TEaUgOSqCX40Q37rGSl9K+rjnboJBYNCmwVp9bfyj
+ kCLL/3g57nTSqhgHNa1xwemePvgNdn6FZteA8sXiCg5ZzaISqWAffek5AoGBAMPw
+ V/vwQ96C8E3l1cH5cUbmBCCcfXM2GLv74bb1V3SvCiAKgOrZ8gEgUiQ0+TfcbAbe
+ 7MM20vRNQjaLTBpai/BTbmqM1Q+r1KNjq8k5bfTdAoGANgzlNM9omM10rd9WagL5
+ yuJcal/03p048mtB4OI4Xr5ZJISHze8fK4jQ5veUT9Vu2Fy/w6QMsuRf+qWeCXR5
+ RPC2H0JzkS+2uZp8BOHk1iDPqbxWXJE9I57CxBV9C/tfzo2IhtOOcuJ4LY+sw+y/
+ ocKpJbdLTWrTLdqLHwicdn8OxeWot1mOukyK2l0UeDkY6H5pYPtHTpAZvRBd7ETL
+ Zs2RP3KFFvho6aIDGrY0wee740/jWotx7fbxxKwPyDRsbH3+1Wx/eX2RND4OGdkH
+ gejJEzpk/7y/P/hCad7bSDdHZwO+Z03HIRC0E8yQz+JYatrqckaRCtd7cXryTmTR
+ FbvLJmECgYBDpfno2CzcFJCTdNBZFi34oJRiDb+HdESXepk58PcNcgK3R8PXf+au
+ OqDBtZIuFv9U1WAg0gzGwt/0Y9u2c8m0nXziUS6AePxy5sBHs7g9C9WeZRz/nCWK
+ +cHIm7XOwBEzDKz5f9eBqRGipm0skDZNKl8X/5QMTT5K3Eci2n+lTw==
+ -----END RSA PRIVATE KEY-----
+
+Public key
+----------
+
+Public key file in "*.pub" format is used to
+verify a
+Â
+digital signature. Public
+key is present on the remote
+side and allows access to
+the owner of the matching private key.
+
+ An example of public key
+format:
+
+ ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQCpujuOiTKCcGkbbBhrk0Hjmezr5QpM0swscXQE7fOZG0oQSURoapd9tjC9eVy5FvZ339jl1WkJkdXSRtjc2G1U5wQh77VE5qJT0ESxQCEw0S+CItWBKqXhC9E7gFY+UyP5YBZcOneh6gGHyCVfK6H215vzKr3x+/WvWl5gZGtbf+zhX6o4RJDRdjZPutYJhEsg/qtMxcCtMjfm/dZTnXeafuebV8nug3RCBUflvRb1XUrJuiX28gsd4xfG/P6L/mNMR8s4kmJEZhlhxpj8Th0iIc+XciVtXuGWQrbddcVRLxAmvkYAPGnVVOQeNj69pqAR/GXaFAhvjYkseEowQao1 username@organization.example.com
+
+### How to add your own key
+
+First, generate a new keypair of your public and private key:
+
+ local $ ssh-keygen -C 'username@organization.example.com' -f additional_key
+
+Please, enter **strong** **passphrase** for securing your private key.
+
+You can insert additional public key into authorized_keys file for
+authentication with your own private key. Additional records in
+authorized_keys file must be delimited by new line. Users are
+not advised to remove the default public key from authorized_keys file.
+
+Example:
+
+ $ cat additional_key.pub > ~/.ssh/authorized_keys
+
+In this example, we add an additional public key, stored in file
+additional_key.pub into the authorized_keys. Next time we log in, we
+will be able to use the private addtional_key key to log in.
+
+### How to remove your own key
+
+Removing your key from authorized_keys can be done simply by deleting
+the corresponding public key which can be identified by a comment at the
+end of line (eg. username@organization.example.com).
+
diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/vpn-connection-fail-in-win-8.1.md b/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/vpn-connection-fail-in-win-8.1.md
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--- /dev/null
+++ b/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/vpn-connection-fail-in-win-8.1.md
@@ -0,0 +1,27 @@
+VPN - Connection fail in Win 8.1
+================================
+
+**Failed to initialize connection subsystem Win 8.1 - 02-10-15 MS patch
+
+AnyConnect users on Windows 8.1 will receive a "Failed to initialize
+connection subsystem" error after installing the Windows 8.1 02/10/15
+security patch. This OS defect introduced with the 02/10/15 patch update
+will also impact WIndows 7 users with IE11. Windows Server
+2008/2012 are also impacted by this defect, but neither is a supported
+OS for AnyConnect.
+
+**Workaround:**
+
+- Close the Cisco AnyConnect Window and the taskbar mini-icon
+- Right click vpnui.exe in the 'Cisco AnyConnect Secure Mobility
+ Client' folder. (C:Program Files (x86)CiscoCisco AnyConnect
+ Secure Mobility
+- Client)
+- Click on the 'Run compatibility troubleshooter' button
+- Choose 'Try recommended settings'
+- The wizard suggests Windows 8 compatibility.
+- Click 'Test Program'. This will open the program.
+- Close
+
+
+
diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/vpnuiV.png b/converted/docs.it4i.cz/get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/vpnuiV.png
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diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/applying-for-resources.md b/converted/docs.it4i.cz/get-started-with-it4innovations/applying-for-resources.md
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+++ b/converted/docs.it4i.cz/get-started-with-it4innovations/applying-for-resources.md
@@ -0,0 +1,38 @@
+Applying for Resources
+======================
+
+
+
+Computational resources may be allocated by any of the following
+[Computing resources
+allocation](http://www.it4i.cz/computing-resources-allocation/?lang=en)
+mechanisms.
+
+Academic researchers can apply for computational resources via [Open
+Access
+Competitions](http://www.it4i.cz/open-access-competition/?lang=en&lang=en).
+
+Anyone is welcomed to apply via the [Directors
+Discretion.](http://www.it4i.cz/obtaining-computational-resources-through-directors-discretion/?lang=en&lang=en)
+
+Foreign (mostly European) users can obtain computational resources via
+the [PRACE (DECI)
+program](http://www.prace-ri.eu/DECI-Projects).
+
+In all cases, IT4Innovations’ access mechanisms are aimed at
+distributing computational resources while taking into account the
+development and application of supercomputing methods and their benefits
+and usefulness for society. The applicants are expected to submit a
+proposal. In the proposal, the applicants **apply for a particular
+amount of core-hours** of computational resources. The requested
+core-hours should be substantiated by scientific excellence of the
+proposal, its computational maturity and expected impacts.
+Proposals do undergo a scientific, technical and economic
+evaluation. The allocation decisions are based on this
+evaluation. More information at [Computing resources
+allocation](http://www.it4i.cz/computing-resources-allocation/?lang=en)
+and [Obtaining Login
+Credentials](obtaining-login-credentials.html) page.
+
+Â
+
diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/obtaining-login-credentials/Authorization_chain.png b/converted/docs.it4i.cz/get-started-with-it4innovations/obtaining-login-credentials/Authorization_chain.png
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diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/obtaining-login-credentials/certificates-faq.md b/converted/docs.it4i.cz/get-started-with-it4innovations/obtaining-login-credentials/certificates-faq.md
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@@ -0,0 +1,304 @@
+Certificates FAQ
+================
+
+FAQ about certificates in general
+
+
+
+Q: What are certificates?
+-------------------------
+
+IT4Innovations employs X.509 certificates for secure communication (e.
+g. credentials exchange) and for grid services related to PRACE, as they
+present a single method of authentication for all PRACE services, where
+only one password is required.
+
+There are different kinds of certificates, each with a different scope
+of use. We mention here:
+
+- User (Private) certificates
+
+- Certificate Authority (CA) certificates
+
+- Host certificates
+
+- Service certificates
+
+Â
+
+**However, users need only manage User and CA certificates. Note that your
+user certificate is protected by an associated private key, and this
+private key must never be disclosed**.
+
+Q: Which X.509 certificates are recognised by IT4Innovations?
+-------------------------------------------------------------
+
+Any certificate that has been issued by a Certification Authority (CA)
+from a member of the IGTF ([http:www.igtf.net](http://www.igtf.net/)) is
+recognised by IT4Innovations: European certificates are issued by
+members of the EUGridPMA
+([https://www.eugridmpa.org](https://www.eugridpma.org/)), which is part
+of the IGTF and coordinates the trust fabric for e-Science Grid
+authentication within Europe. Further the Czech *"Qualified certificate"
+(Kvalifikovaný certifikát)* (provided by <http://www.postsignum.cz/> or
+<http://www.ica.cz/Kvalifikovany-certifikat.aspx>), that is used in
+electronic contact with Czech public authorities is accepted.
+
+Q: How do I get a User Certificate that can be used with IT4Innovations?
+------------------------------------------------------------------------
+
+To get a certificate, you must make a request to your local, IGTF
+approved, Certificate Authority (CA). Usually you then must visit, in
+person, your nearest Registration Authority (RA) to verify your
+affiliation and identity (photo identification is required). Usually,
+you will then be emailed details on how to retrieve your certificate,
+although procedures can vary between CAs. If you are in Europe, you can
+locate your trusted CA via <http://www.eugridpma.org/members/worldmap>.
+
+In some countries certificates can also be retrieved using the TERENA
+Certificate Service, see the FAQ below for the link.
+
+Q: Does IT4Innovations support short lived certificates (SLCS)?
+---------------------------------------------------------------
+
+Yes, provided that the CA which provides this service is also a member
+of IGTF.
+
+Q: Does IT4Innovations support the TERENA certificate service?
+--------------------------------------------------------------
+
+Yes, ITInnovations supports TERENA eScience personal certificates. For
+more information, please visit
+[https://tcs-escience-portal.terena.org](https://tcs-escience-portal.terena.org/){.spip_url
+.spip_out}, where you also can find if your organisation/country can use
+this service
+
+Q: What format should my certificate take?
+------------------------------------------
+
+User Certificates come in many formats, the three most common being the
+’PKCS12’, ’PEM’ and the JKS formats.
+
+The PKCS12 (often abbreviated to ’p12’) format stores your user
+certificate, along with your associated private key, in a single file.
+This form of your certificate is typically employed by web browsers,
+mail clients, and grid services like UNICORE, DART, gsissh-term and
+Globus toolkit (GSI-SSH, GridFTP and GRAM5).
+
+The PEM format (*.pem) stores your user certificate and your associated
+private key in two separate files. This form of your certificate can be
+used by PRACE’s gsissh-term and with the grid related services like
+Globus toolkit (GSI-SSH, GridFTP and GRAM5).
+
+To convert your Certificate from PEM to p12 formats, and *vice versa*,
+IT4Innovations recommends using the openssl tool (see separate FAQ
+entry).
+
+JKS is the Java KeyStore and may contain both your personal certificate
+with your private key and a list of your trusted CA certificates. This
+form of your certificate can be used by grid services like DART and
+UNICORE6.
+
+To convert your Certificate from p12 to JKS, IT4Innovations recommends
+using the keytool utiliy (see separate FAQ entry).
+
+Q: What are CA certificates?
+----------------------------
+
+Certification Authority (CA) certificates are used to verify the link
+between your user certificate and the authority which issued it. They
+are also used to verify the link between the host certificate of a
+IT4Innovations server and the CA which issued that certificate. In
+essence they establish a chain of trust between you and the target
+server. Thus, for some grid services, users must have a copy of all the
+CA certificates.
+
+To assist users, SURFsara (a member of PRACE) provides a complete and
+up-to-date bundle of all the CA certificates that any PRACE user (or
+IT4Innovations grid services user) will require. Bundle of certificates,
+in either p12, PEM or JKS formats, are available from
+<http://winnetou.sara.nl/prace/certs/>.
+
+It is worth noting that gsissh-term and DART automatically updates their
+CA certificates from this SURFsara website. In other cases, if you
+receive a warning that a server’s certificate can not be validated (not
+trusted), then please update your CA certificates via the SURFsara
+website. If this fails, then please contact the IT4Innovations helpdesk.
+
+Lastly, if you need the CA certificates for a personal Globus 5
+installation, then you can install the CA certificates from a MyProxy
+server with the following command.
+
+ myproxy-get-trustroots -s myproxy-prace.lrz.de
+
+If you run this command as ’root’, then it will install the certificates
+into /etc/grid-security/certificates. If you run this not as ’root’,
+then the certificates will be installed into
+$HOME/.globus/certificates. For Globus, you can download the
+globuscerts.tar.gz packet from <http://winnetou.sara.nl/prace/certs/>.
+
+Q: What is a DN and how do I find mine?
+---------------------------------------
+
+DN stands for Distinguished Name and is part of your user certificate.
+IT4Innovations needs to know your DN to enable your account to use the
+grid services. You may use openssl (see below) to determine your DN or,
+if your browser contains your user certificate, you can extract your DN
+from your browser.
+
+For Internet Explorer users, the DN is referred to as the "subject" of
+your certificate. Tools->Internet
+Options->Content->Certificates->View->Details->Subject.
+
+For users running Firefox under Windows, the DN is referred to as the
+"subject" of your certificate.
+Tools->Options->Advanced->Encryption->View Certificates.
+Highlight your name and then Click View->Details->Subject.
+
+Q: How do I use the openssl tool?
+---------------------------------
+
+The following examples are for Unix/Linux operating systems only.
+
+To convert from PEM to p12, enter the following command:
+
+ openssl pkcs12 -export -in usercert.pem -inkey userkey.pem -out
+ username.p12
+
+To convert from p12 to PEM, type the following *four* commands:
+
+ openssl pkcs12 -in username.p12 -out usercert.pem -clcerts -nokeys
+ openssl pkcs12 -in username.p12 -out userkey.pem -nocerts
+ chmod 444 usercert.pem
+ chmod 400 userkey.pem
+
+To check your Distinguished Name (DN), enter the following command:
+
+ openssl x509 -in usercert.pem -noout -subject -nameopt
+ RFC2253
+
+To check your certificate (e.g., DN, validity, issuer, public key
+algorithm, etc.), enter the following command:
+
+ openssl x509 -in usercert.pem -text -noout
+
+To download openssl for both Linux and Windows, please visit
+<http://www.openssl.org/related/binaries.html>. On Macintosh Mac OS X
+computers openssl is already pre-installed and can be used immediately.
+
+Q: How do I create and then manage a keystore?
+----------------------------------------------
+
+IT4innovations recommends the java based keytool utility to create and
+manage keystores, which themselves are stores of keys and certificates.
+For example if you want to convert your pkcs12 formatted key pair into a
+java keystore you can use the following command.
+
+ keytool -importkeystore -srckeystore $my_p12_cert -destkeystore
+ $my_keystore -srcstoretype pkcs12 -deststoretype jks -alias
+ $my_nickname -destalias $my_nickname
+
+where $my_p12_cert is the name of your p12 (pkcs12) certificate,
+$my_keystore is the name that you give to your new java keystore and
+$my_nickname is the alias name that the p12 certificate was given and
+is used also for the new keystore.
+
+You also can import CA certificates into your java keystore with the
+tool, e.g.:
+
+ keytool -import -trustcacerts -alias $mydomain -file $mydomain.crt -keystore $my_keystore
+
+where $mydomain.crt is the certificate of a trusted signing authority
+(CA) and $mydomain is the alias name that you give to the entry.
+
+More information on the tool can be found
+at:<http://docs.oracle.com/javase/7/docs/technotes/tools/solaris/keytool.html>
+
+Q: How do I use my certificate to access the different grid Services?
+---------------------------------------------------------------------
+
+Most grid services require the use of your certificate; however, the
+format of your certificate depends on the grid Service you wish to
+employ.
+
+If employing the PRACE version of GSISSH-term (also a Java Web Start
+Application), you may use either the PEM or p12 formats. Note that this
+service automatically installs up-to-date PRACE CA certificates.
+
+If the grid service is UNICORE, then you bind your certificate, in
+either the p12 format or JKS, to UNICORE during the installation of the
+client on your local machine. For more information, please visit
+[UNICORE6 in PRACE](http://www.prace-ri.eu/UNICORE6-in-PRACE)
+
+If the grid service is part of Globus, such as GSI-SSH, GriFTP or GRAM5,
+then the certificates can be in either p12 or PEM format and must reside
+in the "$HOME/.globus" directory for Linux and Mac users or
+%HOMEPATH%.globus for Windows users. (Windows users will have to use
+the DOS command ’cmd’ to create a directory which starts with a ’.’).
+Further, user certificates should be named either "usercred.p12" or
+"usercert.pem" and "userkey.pem", and the CA certificates must be kept
+in a pre-specified directory as follows. For Linux and Mac users, this
+directory is either $HOME/.globus/certificates or
+/etc/grid-security/certificates. For Windows users, this directory is
+%HOMEPATH%.globuscertificates. (If you are using GSISSH-Term from
+prace-ri.eu then you do not have to create the .globus directory nor
+install CA certificates to use this tool alone).
+
+Q: How do I manually import my certificate into my browser?
+-----------------------------------------------------------
+
+If you employ the Firefox browser, then you can import your certificate
+by first choosing the "Preferences" window. For Windows, this is
+Tools->Options. For Linux, this is Edit->Preferences. For Mac,
+this is Firefox->Preferences. Then, choose the "Advanced" button;
+followed by the "Encryption" tab. Then, choose the "Certificates" panel;
+select the option "Select one automatically" if you have only one
+certificate, or "Ask me every time" if you have more then one. Then
+click on the "View Certificates" button to open the "Certificate
+Manager" window. You can then select the "Your Certificates" tab and
+click on button "Import". Then locate the PKCS12 (.p12) certificate you
+wish to import, and employ its associated password.
+
+If you are a Safari user, then simply open the "Keychain Access"
+application and follow "File->Import items".
+
+If you are an Internet Explorer user, click
+Start->Settings->Control Panel and then double-click on Internet.
+On the Content tab, click Personal, and then click Import. In the
+Password box, type your password. NB you may be prompted multiple times
+for your password. In the "Certificate File To Import" box, type the
+filename of the certificate you wish to import, and then click OK. Click
+Close, and then click OK.
+
+Q: What is a proxy certificate?
+-------------------------------
+
+A proxy certificate is a short-lived certificate which may be employed
+by UNICORE and the Globus services. The proxy certificate consists of a
+new user certificate and a newly generated proxy private key. This proxy
+typically has a rather short lifetime (normally 12 hours) and often only
+allows a limited delegation of rights. Its default location, for
+Unix/Linux, is /tmp/x509_u*uid* but can be set via the
+$X509_USER_PROXY environment variable.
+
+Q: What is the MyProxy service?
+-------------------------------
+
+[The MyProxy Service](http://grid.ncsa.illinois.edu/myproxy/)
+, can be employed by gsissh-term and Globus tools, and is
+an online repository that allows users to store long lived proxy
+certificates remotely, which can then be retrieved for use at a later
+date. Each proxy is protected by a password provided by the user at the
+time of storage. This is beneficial to Globus users as they do not have
+to carry their private keys and certificates when travelling; nor do
+users have to install private keys and certificates on possibly insecure
+computers.
+
+Q: Someone may have copied or had access to the private key of my certificate either in a separate file or in the browser. What should I do?
+--------------------------------------------------------------------------------------------------------------------------------------------
+
+Please ask the CA that issued your certificate to revoke this certifcate
+and to supply you with a new one. In addition, please report this to
+IT4Innovations by contacting [the support
+team](https://support.it4i.cz/rt).
+
diff --git a/converted/docs.it4i.cz/get-started-with-it4innovations/obtaining-login-credentials/obtaining-login-credentials.md b/converted/docs.it4i.cz/get-started-with-it4innovations/obtaining-login-credentials/obtaining-login-credentials.md
new file mode 100644
index 0000000000000000000000000000000000000000..3cbe8e759f76b67c6eabb4c69281a50d0b436915
--- /dev/null
+++ b/converted/docs.it4i.cz/get-started-with-it4innovations/obtaining-login-credentials/obtaining-login-credentials.md
@@ -0,0 +1,266 @@
+Obtaining Login Credentials
+===========================
+
+
+
+Obtaining Authorization
+-----------------------
+
+The computational resources of IT4I Â are allocated by the Allocation
+Committee to a [Project](../introduction.html),
+investigated by a Primary Investigator. By allocating the computational
+resources, the Allocation Committee is authorizing the PI to access and
+use the clusters. The PI may decide to authorize a number of her/his
+Collaborators to access and use the clusters, to consume the resources
+allocated to her/his Project. These collaborators will be associated to
+the Project. The Figure below is depicting the authorization chain:
+
+
+
+Â You need to either [become the
+PI](../applying-for-resources.html) or [be named as a
+collaborator](obtaining-login-credentials.html#authorization-of-collaborator-by-pi)
+by a PI in order to access and use the clusters.
+
+Head of Supercomputing Services acts as a PI of a project DD-13-5.
+Joining this project, you may **access and explore the clusters**, use
+software, development environment and computers via the qexp and qfree
+queues. You may use these resources for own education/research, no
+paperwork is required. All IT4I employees may contact the Head of
+Supercomputing Services in order to obtain **free access to the
+clusters**.
+
+### Authorization of PI by Allocation Committee
+
+The PI is authorized to use the clusters by the allocation decision
+issued by the Allocation Committee.The PI will be informed by IT4I about
+the Allocation Committee decision.
+
+### Authorization by web
+
+This is a preferred way of granting access to project resources.
+Please, use this method whenever it's possible.
+
+Log in to the [IT4I Extranet
+portal](https://extranet.it4i.cz) using IT4I credentials
+and go to the **Projects** section.
+
+- **Users:** Please, submit your requests for becoming a
+ project member.
+- **Primary Investigators:** Please, approve or deny users' requests
+ in the same section.
+
+### Authorization by e-mail (an alternative approach)
+
+Â In order to authorize a Collaborator to utilize the allocated
+resources, the PI should contact the [IT4I
+support](https://support.it4i.cz/rt/) (E-mail: [support
+[at] it4i.cz](mailto:support%20%5Bat%5D%20it4i.cz)) and provide
+following information:
+
+1. Identify your project by project ID
+2. Provide list of people, including himself, who are authorized to use
+ the resources allocated to the project. The list must include full
+ name, e-mail and affiliation. Provide usernames as well, ifÂ
+ collaborator login access already exists on the IT4I systems.
+3. Include "Authorization to IT4Innovations" into the subject line.
+
+Example (except the subject line which must be in English, you may use
+Czech or Slovak language for communication with us):
+
+ Subject: Authorization to IT4Innovations
+
+ Dear support,
+
+ Please include my collaborators to project OPEN-0-0.
+
+ John Smith, john.smith@myemail.com, Department of Chemistry, MIT, US
+ Jonas Johansson, jjohansson@otheremail.se, Department of Physics, Royal Institute of Technology, Sweden
+ Luisa Fibonacci, lf@emailitalia.it, Department of Mathematics, National Research Council, Italy
+
+ Thank you,
+ PI
+ (Digitally signed)
+
+Should the above information be provided by e-mail, the e-mail **must
+be** digitally signed. Read more on [digital
+signatures](obtaining-login-credentials.html#the-certificates-for-digital-signatures)
+below.
+
+The Login Credentials
+-------------------------
+
+Once authorized by PI, every person (PI or Collaborator) wishing to
+access the clusters, should contact the [IT4I
+support](https://support.it4i.cz/rt/) (E-mail: [support
+[at] it4i.cz](mailto:support%20%5Bat%5D%20it4i.cz)) providing
+following information:
+
+1. Project ID
+2. Full name and affiliation
+3. Statement that you have read and accepted the [Acceptable use policy
+ document](http://www.it4i.cz/acceptable-use-policy.pdf) (AUP).
+4. Attach the AUP file.
+5. Your preferred username, max 8 characters long. The preferred
+ username must associate your surname and name or be otherwise
+ derived from it. Only alphanumeric sequences, dash and underscore
+ signs are allowed.
+6. In case you choose [Alternative way to personal
+ certificate](obtaining-login-credentials.html#alternative-way-of-getting-personal-certificate),
+ a **scan of photo ID** (personal ID or passport or driver license)
+ is required
+
+Example (except the subject line which must be in English, you may use
+Czech or Slovak language for communication with us):
+
+ Subject: Access to IT4Innovations
+
+ Dear support,
+
+ Please open the user account for me and attach the account to OPEN-0-0
+ Name and affiliation: John Smith, john.smith@myemail.com, Department of Chemistry, MIT, US
+ I have read and accept the Acceptable use policy document (attached)
+
+ Preferred username: johnsm
+
+ Thank you,
+ John Smith
+ (Digitally signed)
+
+Should the above information be provided by e-mail, the e-mail **must
+be** digitally signed. To sign an e-mail, you need digital certificate.
+Read more on [digital
+signatures](obtaining-login-credentials.html#the-certificates-for-digital-signatures)
+below.
+
+Digital signature allows us to confirm your identity in remote
+electronic communication and provides an encrypted channel to exchange
+sensitive information such as login credentials. After receiving your
+signed e-mail with the requested information, we will send you your
+login credentials (user name, key, passphrase and password) to access
+the IT4I systems.
+
+We accept certificates issued by any widely respected certification
+authority.
+
+For various reasons we do not accept PGP keys.** Please, use only
+X.509 PKI certificates for communication with us.**
+
+You will receive your personal login credentials by protected e-mail.
+The login credentials include:
+
+1. username
+2. ssh private key and private key passphrase
+3. system password
+
+The clusters are accessed by the [private
+key](../accessing-the-clusters/shell-access-and-data-transfer/ssh-keys.html)
+and username.
+Username and password is used for login to the information systems
+listed on <http://support.it4i.cz/>.
+
+### Change Passphrase
+
+On Linux, use
+
+`
+local $ ssh-keygen -f id_rsa -p
+`
+
+On Windows, use [PuTTY Key
+Generator](../accessing-the-clusters/shell-access-and-data-transfer/putty/puttygen.html).
+
+### Change Password
+
+Change password in your user profile atÂ
+<https://extranet.it4i.cz/user/>
+
+The Certificates for Digital Signatures
+-------------------------------------------
+
+We accept personal certificates issued by any widely respected
+certification authority (CA). This includes certificates by CAs
+organized in International Grid Trust Federation
+(<http://www.igtf.net/>), its European branch EUGridPMA -
+<https://www.eugridpma.org/> and its member organizations, e.g. the
+CESNET certification authority - <https://tcs-p.cesnet.cz/confusa/>. The
+Czech *"Qualified certificate" (Kvalifikovaný certifikát)* (provided by
+<http://www.postsignum.cz/> or
+<http://www.ica.cz/Kvalifikovany-certifikat.aspx>), that is used in
+electronic contact with Czech authorities is accepted as well.
+
+Certificate generation process is well-described here:
+
+- [How to generate a personal TCS certificate in Mozilla Firefox web
+ browser
+ (in Czech)](http://idoc.vsb.cz/xwiki/wiki/infra/view/uzivatel/moz-cert-gen)
+
+Â
+
+A FAQ about certificates can be found here: >[Certificates
+FAQ](certificates-faq.html).
+
+Alternative Way to Personal Certificate
+-------------------------------------------
+
+Follow these steps **only** if you can not obtain your certificate in a
+standard way.
+In case you choose this procedure, please attach a **scan of photo ID**
+(personal ID or passport or drivers license) when applying for [login
+credentials](obtaining-login-credentials.html#the-login-credentials).
+
+1. Go to <https://www.cacert.org/>.
+ - If there's a security warning, just acknowledge it.
+
+2. Click *Join*.
+3. Fill in the form and submit it by the *Next* button.
+ - Type in the e-mail address which you use for communication
+ with us.
+ - Don't forget your chosen *Pass Phrase*.
+
+4. You will receive an e-mail verification link. Follow it.
+5. After verifying, go to the CAcert's homepage and login using
+ *Password Login*.
+6. Go to *Client Certificates* -> *New*.
+7. Tick *Add* for your e-mail address and click the *Next* button.
+8. Click the *Create Certificate Request* button.
+9. You'll be redirected to a page from where you can download/install
+ your certificate.
+ - Simultaneously you'll get an e-mail with a link to
+ the certificate.
+
+Installation of the Certificate Into Your Mail Client
+-----------------------------------------------------
+
+The procedure is similar to the following guides:
+
+- MS Outlook 2010
+ - [How to Remove, Import, and Export Digital
+ Certificates](http://support.microsoft.com/kb/179380)
+ - [Importing a PKCS #12 certificate
+ (in Czech)](http://idoc.vsb.cz/xwiki/wiki/infra/view/uzivatel/outl-cert-imp)
+- Mozilla Thudnerbird
+ - [Installing an SMIME
+ certificate](http://kb.mozillazine.org/Installing_an_SMIME_certificate)
+ - [Importing a PKCS #12 certificate
+ (in Czech)](http://idoc.vsb.cz/xwiki/wiki/infra/view/uzivatel/moz-cert-imp)
+
+End of User Account Lifecycle
+-----------------------------
+
+User accounts are supported by membership in active Project(s) or by
+affiliation to IT4Innovations. User accounts, that loose the support
+(meaning, are not attached to an active project and are not affiliated
+with IT4I), will be deleted 1 year after the last project to which they
+were attached expires.
+
+User will get 3 automatically generated warning e-mail messages of the
+pending removal:.
+
+- First message will be sent 3 months before the removal
+- Second message will be sent 1 month before the removal
+- Third message will be sent 1 week before the removal.
+
+The messages will inform about the projected removal date and will
+challenge the user to migrate her/his data
+
diff --git a/converted/docs.it4i.cz/index.md b/converted/docs.it4i.cz/index.md
new file mode 100644
index 0000000000000000000000000000000000000000..f99c494d9c204a5832fe1c55d520658ef12b5a1c
--- /dev/null
+++ b/converted/docs.it4i.cz/index.md
@@ -0,0 +1,144 @@
+Documentation
+=============
+
+
+
+Welcome to IT4Innovations documentation pages. The IT4Innovations
+national supercomputing center operates supercomputers
+[Salomon](salomon.html) and
+[Anselm](anselm.html). The supercomputers are [
+available](get-started-with-it4innovations/applying-for-resources.html)
+to academic community within the Czech Republic and Europe and
+industrial community worldwide. The purpose of these pages is to provide
+a comprehensive documentation on hardware, software and usage of the
+computers.
+
+ How to read the documentation
+--------------------------------------------------------------------------------------------------
+
+1. Read the list in the left column. Select the subject of interest.
+ Alternatively, use the Search box in the upper right corner.
+2. Read the CONTENTS in the upper right corner.
+3. Scan for all the yellow bulb call-outs on the page.
+4. Read the details if still more information is needed. **Look for
+ examples** illustrating the concepts.
+
+Â
+
+The call-out. Â Focus on the call-outs before reading full details.
+
+Â
+
+- Read the
+ [Changelog](get-started-with-it4innovations/changelog.html)
+ to keep up to date.
+
+Getting Help and Support
+------------------------
+
+Contact [support [at]
+it4i.cz](mailto:support%20%5Bat%5D%20it4i.cz) for help and
+support regarding the cluster technology at IT4Innovations.
+Please use **Czech**, **Slovak** or **English** language for
+communication with us.
+Follow the status of your request to IT4Innovations at
+[support.it4i.cz/rt](http://support.it4i.cz/rt).
+
+Â
+
+Use your IT4Innotations username and password to log in to the
+[support](http://support.it4i.cz/) portal.
+
+Required Proficiency
+--------------------
+
+You need basic proficiency in Linux environment.
+
+Â
+
+In order to use the system for your calculations, you need basic
+proficiency in Linux environment. To gain the proficiency, we recommend
+you reading the [ introduction to
+Linux](http://www.tldp.org/LDP/intro-linux/html/)
+operating system environment and installing a Linux distribution on your
+personal computer. A good choice might be the [
+Fedora](http://fedoraproject.org/)
+distribution, as it is similar to systems on the clusters at
+IT4Innovations. It's easy to install and use. In fact, any distribution
+would do.
+
+Â
+
+Learn how to parallelize your code!
+
+Â
+
+In many cases, you will run your own code on the cluster. In order to
+fully exploit the cluster, you will need to carefully consider how to
+utilize all the cores available on the node and how to use multiple
+nodes at the same time. You need to **parallelize** your code.
+Proficieny in MPI, OpenMP, CUDA, UPC or GPI2 programming may be gained
+via the [training provided by
+IT4Innovations.](http://prace.it4i.cz)
+
+Terminology Frequently Used on These Pages
+------------------------------------------
+
+- **node:** a computer, interconnected by network to other computers -
+ Computational nodes are powerful computers, designed and dedicated
+ for executing demanding scientific computations.
+- **core:** processor core, a unit of processor, executing
+ computations
+- **corehours:** wall clock hours of processor core time - Each node
+ is equipped with **X** processor cores, provides **X** corehours per
+ 1 wall clock hour.
+- **job:** a calculation running on the supercomputer - The job
+ allocates and utilizes resources of the supercomputer for
+ certain time.
+- **HPC:** High Performance Computing
+- **HPC (computational) resources:** corehours, storage capacity,
+ software licences
+- **code:** a program
+- **primary investigator (PI):** a person responsible for execution of
+ computational project and utilization of computational resources
+ allocated to that project
+- **collaborator:** a person participating on execution of
+ computational project and utilization of computational resources
+ allocated to that project
+- **project:** a computational project under investigation by the
+ PI - The project is identified by the project ID. The computational
+ resources are allocated and charged per project.
+- **jobscript:** a script to be executed by the PBS Professional
+ workload manager
+
+Conventions
+-----------
+
+In this documentation, you will find a number of pages containing
+examples. We use the following conventions:
+
+Â Cluster command prompt
+
+`
+$
+`
+
+Your local linux host command prompt
+
+`
+local $
+`
+
+Â Errata
+-------
+
+Although we have taken every care to ensure the accuracy of our content,
+mistakes do happen. If you find a mistake in the text or the code we
+would be grateful if you would report this to us. By doing so, you can
+save other readers from frustration and help us improve subsequent
+versions of this documentation. If you find any errata, please report
+them by visiting http://support.it4i.cz/rt, creating a new ticket, and
+entering the details of your errata. Once your errata are verified, your
+submission will be accepted and the errata will be uploaded on our
+website.
+
diff --git a/converted/docs.it4i.cz/salomon/accessing-the-cluster.md b/converted/docs.it4i.cz/salomon/accessing-the-cluster.md
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@@ -0,0 +1,143 @@
+Shell access and data transfer
+==============================
+
+
+
+Interactive Login
+-----------------
+
+The Salomon cluster is accessed by SSH protocol via login nodes login1,
+login2, login3 and login4 at address salomon.it4i.cz. The login nodes
+may be addressed specifically, by prepending the login node name to the
+address.
+
+The alias >salomon.it4i.cz is currently not available through VPN
+connection. Please use loginX.salomon.it4i.cz when connected to
+VPN.
+
+ |Login address|Port|Protocol|Login node|
+ |---|---|---|---|
+ |salomon.it4i.cz|22|ssh|round-robin DNS record for login[1-4]|
+ |login1.salomon.it4i.cz|22|ssh|login1|
+ |login1.salomon.it4i.cz|22|ssh|login1|
+ |login1.salomon.it4i.cz|22|ssh|login1|
+ |login1.salomon.it4i.cz|22|ssh|login1|
+
+The authentication is by the [private
+key](../get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/ssh-keys.html)
+
+Please verify SSH fingerprints during the first logon. They are
+identical on all login nodes:
+f6:28:98:e4:f9:b2:a6:8f:f2:f4:2d:0a:09:67:69:80Â (DSA)
+70:01:c9:9a:5d:88:91:c7:1b:c0:84:d1:fa:4e:83:5c (RSA)
+
+Â
+
+Private key (`id_rsa/id_rsa.ppk` ): `600 (-rw-------)`s authentication:
+
+On **Linux** or **Mac**, use
+
+`
+local $ ssh -i /path/to/id_rsa username@salomon.it4i.cz
+`
+
+If you see warning message "UNPROTECTED PRIVATE KEY FILE!", use this
+command to set lower permissions to private key file.
+
+`
+local $ chmod 600 /path/to/id_rsa
+`
+
+On **Windows**, use [PuTTY ssh
+client](../get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/putty/putty.html).
+
+After logging in, you will see the command prompt:
+
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â _____Â Â Â Â Â Â _Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â / ____|Â Â Â Â | |Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â | (___Â Â __ _| | ___Â _ __ ___Â Â ___Â _ __ Â
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â ___ / _` | |/ _ | '_ ` _ / _ | '_
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â ____) | (_| | | (_) | | | | | | (_) | | | |
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â |_____/ __,_|_|___/|_| |_| |_|___/|_| |_|
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â
+
+ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â http://www.it4i.cz/?lang=en
+
+ Last login: Tue Jul 9 15:57:38 2013 from your-host.example.com
+ [username@login2.salomon ~]$
+
+The environment is **not** shared between login nodes, except for
+[shared filesystems](storage/storage.html).
+
+Data Transfer
+-------------
+
+Data in and out of the system may be transferred by the
+[scp](http://en.wikipedia.org/wiki/Secure_copy) and sftp
+protocols.
+
+In case large volumes of data are transferred, use dedicated data mover
+nodes cedge[1-3].salomon.it4i.cz for increased performance.
+
+Â
+
+HTML commented section #1 (removed cedge servers from the table)
+
+ Address |Port|Protocol|
+ ----------------------- |---|---|------------
+ salomon.it4i.cz 22 scp, sftp
+ login1.salomon.it4i.cz 22 scp, sftp
+ login2.salomon.it4i.cz 22 scp, sftp
+ login3.salomon.it4i.cz 22 scp, sftp
+ login4.salomon.it4i.cz 22 scp, sftp
+
+Â The authentication is by the [private
+key](../get-started-with-it4innovations/accessing-the-clusters/shell-access-and-data-transfer/ssh-keys.html)
+
+HTML commented section #2 (ssh transfer performance data need to be
+verified)
+
+On linux or Mac, use scp or sftp client to transfer the data to Salomon:
+
+`
+local $ scp -i /path/to/id_rsa my-local-file username@salomon.it4i.cz:directory/file
+`
+
+`
+local $ scp -i /path/to/id_rsa -r my-local-dir username@salomon.it4i.cz:directory
+`
+
+ or
+
+`
+local $ sftp -o IdentityFile=/path/to/id_rsa username@salomon.it4i.cz
+`
+
+Very convenient way to transfer files in and out of the Salomon computer
+is via the fuse filesystem
+[sshfs](http://linux.die.net/man/1/sshfs)
+
+`
+local $ sshfs -o IdentityFile=/path/to/id_rsa username@salomon.it4i.cz:. mountpoint
+`
+
+Using sshfs, the users Salomon home directory will be mounted on your
+local computer, just like an external disk.
+
+Learn more on ssh, scp and sshfs by reading the manpages
+
+`
+$ man ssh
+$ man scp
+$ man sshfs
+`
+
+On Windows, use [WinSCP
+client](http://winscp.net/eng/download.php) to transfer
+the data. The [win-sshfs
+client](http://code.google.com/p/win-sshfs/) provides a
+way to mount the Salomon filesystems directly as an external disc.
+
+More information about the shared file systems is available
+[here](storage/storage.html).
+
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@@ -0,0 +1,118 @@
+Outgoing connections
+====================
+
+
+
+Connection restrictions
+-----------------------
+
+Outgoing connections, from Salomon Cluster login nodes to the outside
+world, are restricted to following ports:
+
+ |Port|Protocol|
+ |---|---|
+ |22|ssh|
+ |80|http|
+ |443|https|
+ |9418|git|
+
+Please use **ssh port forwarding** and proxy servers to connect from
+Salomon to all other remote ports.
+
+Outgoing connections, from Salomon Cluster compute nodes are restricted
+to the internal network. Direct connections form compute nodes to
+outside world are cut.
+
+Port forwarding
+---------------
+
+### Port forwarding from login nodes
+
+Port forwarding allows an application running on Salomon to connect to
+arbitrary remote host and port.
+
+It works by tunneling the connection from Salomon back to users
+workstation and forwarding from the workstation to the remote host.
+
+Pick some unused port on Salomon login node (for example 6000) and
+establish the port forwarding:
+
+`
+local $ ssh -R 6000:remote.host.com:1234 salomon.it4i.cz
+`
+
+In this example, we establish port forwarding between port 6000 on
+Salomon and port 1234 on the remote.host.com. By accessing
+localhost:6000 on Salomon, an application will see response of
+remote.host.com:1234. The traffic will run via users local workstation.
+
+Port forwarding may be done **using PuTTY** as well. On the PuTTY
+Configuration screen, load your Salomon configuration first. Then go to
+Connection->SSH->Tunnels to set up the port forwarding. Click
+Remote radio button. Insert 6000 to Source port textbox. Insert
+remote.host.com:1234. Click Add button, then Open.
+
+Port forwarding may be established directly to the remote host. However,
+this requires that user has ssh access to remote.host.com
+
+`
+$ ssh -L 6000:localhost:1234 remote.host.com
+`
+
+Note: Port number 6000 is chosen as an example only. Pick any free port.
+
+### Port forwarding from compute nodes
+
+Remote port forwarding from compute nodes allows applications running on
+the compute nodes to access hosts outside Salomon Cluster.
+
+First, establish the remote port forwarding form the login node, as
+[described
+above](outgoing-connections.html#port-forwarding-from-login-nodes).
+
+Second, invoke port forwarding from the compute node to the login node.
+Insert following line into your jobscript or interactive shell
+
+`
+$ ssh -TN -f -L 6000:localhost:6000 login1
+`
+
+In this example, we assume that port forwarding from login1:6000 to
+remote.host.com:1234 has been established beforehand. By accessing
+localhost:6000, an application running on a compute node will see
+response of remote.host.com:1234
+
+### Using proxy servers
+
+Port forwarding is static, each single port is mapped to a particular
+port on remote host. Connection to other remote host, requires new
+forward.
+
+Applications with inbuilt proxy support, experience unlimited access to
+remote hosts, via single proxy server.
+
+To establish local proxy server on your workstation, install and run
+SOCKS proxy server software. On Linux, sshd demon provides the
+functionality. To establish SOCKS proxy server listening on port 1080
+run:
+
+`
+local $ ssh -D 1080 localhost
+`
+
+On Windows, install and run the free, open source [Sock
+Puppet](http://sockspuppet.com/) server.
+
+Once the proxy server is running, establish ssh port forwarding from
+Salomon to the proxy server, port 1080, exactly as [described
+above](outgoing-connections.html#port-forwarding-from-login-nodes).
+
+`
+local $ ssh -R 6000:localhost:1080 salomon.it4i.cz
+`
+
+Now, configure the applications proxy settings to **localhost:6000**.
+Use port forwarding to access the [proxy server from compute
+nodes](outgoing-connections.html#port-forwarding-from-compute-nodes)
+as well .
+
diff --git a/converted/docs.it4i.cz/salomon/accessing-the-cluster/vpn-access.md b/converted/docs.it4i.cz/salomon/accessing-the-cluster/vpn-access.md
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@@ -0,0 +1,108 @@
+VPN Access
+==========
+
+
+
+Accessing IT4Innovations internal resources via VPN
+---------------------------------------------------
+
+For using resources and licenses which are located at IT4Innovations
+local network, it is necessary to VPN connect to this network.
+We use Cisco AnyConnect Secure Mobility Client, which is supported on
+the following operating systems:
+
+- >Windows XP
+- >Windows Vista
+- >Windows 7
+- >Windows 8
+- >Linux
+- >MacOS
+
+It is impossible to connect to VPN from other operating systems.
+
+VPN client installation
+------------------------------------
+
+You can install VPN client from web interface after successful login
+with LDAP credentials on address <https://vpn.it4i.cz/user>
+
+
+
+According to the Java settings after login, the client either
+automatically installs, or downloads installation file for your
+operating system. It is necessary to allow start of installation tool
+for automatic installation.
+
+
+
+
+
+
+After successful installation, VPN connection will be established and
+you can use available resources from IT4I network.
+
+
+
+If your Java setting doesn't allow automatic installation, you can
+download installation file and install VPN client manually.
+
+
+
+After you click on the link, download of installation file will start.
+
+
+
+After successful download of installation file, you have to execute this
+tool with administrator's rights and install VPN client manually.
+
+Working with VPN client
+-----------------------
+
+You can use graphical user interface or command line interface to run
+VPN client on all supported operating systems. We suggest using GUI.
+
+Before the first login to VPN, you have to fill
+URLÂ **https://vpn.it4i.cz/user** into the text field.
+
+ Contacting
+
+
+After you click on the Connect button, you must fill your login
+credentials.
+
+ Contacting
+
+
+After a successful login, the client will minimize to the system tray.
+If everything works, you can see a lock in the Cisco tray icon.
+
+[
+
+
+If you right-click on this icon, you will see a context menu in which
+you can control the VPN connection.
+
+[
+
+
+When you connect to the VPN for the first time, the client downloads the
+profile and creates a new item "IT4I cluster" in the connection list.
+For subsequent connections, it is not necessary to re-enter the URL
+address, but just select the corresponding item.
+
+ Contacting
+
+
+Then AnyConnect automatically proceeds like in the case of first logon.
+
+
+
+After a successful logon, you can see a green circle with a tick mark on
+the lock icon.
+
+ Succesfull
+
+
+For disconnecting, right-click on the AnyConnect client icon in the
+system tray and select **VPN Disconnect**.
+
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@@ -0,0 +1,161 @@
+Environment and Modules
+=======================
+
+
+
+### Environment Customization
+
+After logging in, you may want to configure the environment. Write your
+preferred path definitions, aliases, functions and module loads in the
+.bashrc file
+
+`
+# ./bashrc
+
+# Source global definitions
+if [ -f /etc/bashrc ]; then
+ . /etc/bashrc
+fi
+
+# User specific aliases and functions
+alias qs='qstat -a'
+module load intel/2015b
+
+# Display informations to standard output - only in interactive ssh session
+if [ -n "$SSH_TTY" ]
+then
+ module list # Display loaded modules
+fi
+`
+
+Do not run commands outputing to standard output (echo, module list,
+etc) in .bashrc for non-interactive SSH sessions. It breaks fundamental
+functionality (scp, PBS) of your account! Take care for SSH session
+interactivity for such commands as
+ stated in the previous example.
+in the previous example.
+
+### Application Modules
+
+In order to configure your shell for running particular application on
+Salomon we use Module package interface.
+
+Application modules on Salomon cluster are built using
+[EasyBuild](http://hpcugent.github.io/easybuild/ "EasyBuild"). The
+modules are divided into the following structure:
+
+`
+ base: Default module class
+ bio: Bioinformatics, biology and biomedical
+ cae: Computer Aided Engineering (incl. CFD)
+ chem: Chemistry, Computational Chemistry and Quantum Chemistry
+ compiler: Compilers
+ data: Data management & processing tools
+ debugger: Debuggers
+ devel: Development tools
+ geo: Earth Sciences
+ ide: Integrated Development Environments (e.g. editors)
+ lang: Languages and programming aids
+ lib: General purpose libraries
+ math: High-level mathematical software
+ mpi: MPI stacks
+ numlib: Numerical Libraries
+ perf: Performance tools
+ phys: Physics and physical systems simulations
+ system: System utilities (e.g. highly depending on system OS and hardware)
+ toolchain: EasyBuild toolchains
+ tools: General purpose tools
+ vis: Visualization, plotting, documentation and typesetting
+`
+
+The modules set up the application paths, library paths and environment
+variables for running particular application.
+
+The modules may be loaded, unloaded and switched, according to momentary
+needs.
+
+To check available modules use
+
+`
+$ module avail
+`
+
+To load a module, for example the OpenMPI module use
+
+`
+$ module load OpenMPI
+`
+
+loading the OpenMPI module will set up paths and environment variables
+of your active shell such that you are ready to run the OpenMPI software
+
+To check loaded modules use
+
+`
+$ module list
+`
+
+Â To unload a module, for example the OpenMPI module use
+
+`
+$ module unload OpenMPI
+`
+
+Learn more on modules by reading the module man page
+
+`
+$ man module
+`
+
+### EasyBuild Toolchains
+
+As we wrote earlier, we are using EasyBuild for automatised software
+installation and module creation.Â
+
+EasyBuild employs so-called **compiler toolchains** or,
+simply toolchains for short, which are a major concept in handling the
+build and installation processes.
+
+A typical toolchain consists of one or more compilers, usually put
+together with some libraries for specific functionality, e.g., for using
+an MPI stack for distributed computing, or which provide optimized
+routines for commonly used math operations, e.g., the well-known
+BLAS/LAPACK APIs for linear algebra routines.
+
+For each software package being built, the toolchain to be used must be
+specified in some way.
+
+The EasyBuild framework prepares the build environment for the different
+toolchain components, by loading their respective modules and defining
+environment variables to specify compiler commands (e.g.,
+via `$F90`), compiler and linker options (e.g.,
+via `$CFLAGS` and `$LDFLAGS`{.docutils .literal}),
+the list of library names to supply to the linker (via `$LIBS`{.docutils
+.literal}), etc. This enables making easyblocks
+largely toolchain-agnostic since they can simply rely on these
+environment variables; that is, unless they need to be aware of, for
+example, the particular compiler being used to determine the build
+configuration options.
+
+Recent releases of EasyBuild include out-of-the-box toolchain support
+for:
+
+- various compilers, including GCC, Intel, Clang, CUDA
+- common MPI libraries, such as Intel MPI, MPICH, MVAPICH2, OpenMPI
+- various numerical libraries, including ATLAS, Intel MKL, OpenBLAS,
+ ScalaPACK, FFTW
+
+Â
+
+On Salomon, we have currently following toolchains installed:
+
+ |Toolchain|Module(s)|
+ |---|----|
+ |GCC|GCC|
+ |ictce|icc, ifort, imkl, impi|
+ |intel|GCC, icc, ifort, imkl, impi|
+ |gompi|GCC, OpenMPI|
+ |goolf|BLACS, FFTW, GCC, OpenBLAS, OpenMPI, ScaLAPACK|
+ |iompi|OpenMPI, icc, ifort|
+ |iccifort|icc, ifort|
+
diff --git a/converted/docs.it4i.cz/salomon/hardware-overview-1/hardware-overview.md b/converted/docs.it4i.cz/salomon/hardware-overview-1/hardware-overview.md
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@@ -0,0 +1,89 @@
+Hardware Overview
+=================
+
+
+
+Introduction
+------------
+
+The Salomon cluster consists of 1008 computational nodes of which 576
+are regular compute nodes and 432 accelerated nodes. Each node is a
+ powerful x86-64 computer, equipped
+with 24 cores (two twelve-core Intel Xeon processors) and 128GB RAM. The
+nodes are interlinked by high speed InfiniBand and Ethernet networks.
+All nodes share 0.5PB /home NFS disk storage to store the user files.
+Users may use a DDN Lustre shared storage with capacity of 1.69 PB which
+is available for the scratch project data. The user access to the
+Salomon cluster is provided by four login nodes.
+
+[More about schematic representation of the Salomon cluster compute
+nodes IB
+topology](../network-1/ib-single-plane-topology.html).
+
+
+
+The parameters are summarized in the following tables:
+
+General information
+-------------------
+
+In general**
+Primary purpose
+High Performance Computing
+Architecture of compute nodes
+x86-64
+Operating system
+CentOS 6.7 Linux
+[**Compute nodes**](../compute-nodes.html)
+Totally
+1008
+Processor
+2x Intel Xeon E5-2680v3, 2.5GHz, 12cores
+RAM
+128GB, 5.3GB per core, DDR4@2133 MHz
+Local disk drive
+no
+Compute network / Topology
+InfiniBand FDR56 / 7D Enhanced hypercube
+w/o accelerator
+576
+MIC accelerated
+432
+In total**
+Total theoretical peak performance (Rpeak)
+2011 Tflop/s
+Total amount of RAM
+129.024 TB
+Compute nodes
+-------------
+
+ |Node|Count|Processor|Cores|Memory|Accelerator|
+ ----------------- - |---|---|------------------------ ------- -------- --------------------------------------------
+ |w/o accelerator|576|2x Intel Xeon E5-2680v3, 2.5GHz|24|128GB|-|
+ |MIC accelerated|432|2x Intel Xeon E5-2680v3, 2.5GHz|24|128GB|2x Intel Xeon Phi 7120P, 61cores, 16GB RAM|
+
+For more details please refer to the [Compute
+nodes](../compute-nodes.html).
+
+Remote visualization nodes
+--------------------------
+
+For remote visualization two nodes with NICE DCV software are available
+each configured:
+
+ |Node|Count|Processor|Cores|Memory|GPU Accelerator|
+ --------------- - |---|---|----------------------- ------- -------- ------------------------------
+ |visualization|2|2x Intel Xeon E5-2695v3, 2.3GHz|28|512GB|NVIDIA QUADRO K5000, 4GB RAM|
+
+SGI UV 2000
+-----------
+
+For large memory computations a special SMP/NUMA SGI UV 2000 server is
+available:
+
+ |Node |Count |Processor |Cores<th align="left">Memory<th align="left">Extra HW |
+ | --- | --- |
+ |UV2000 |1 |14x Intel Xeon E5-4627v2, 3.3GHz, 8cores |112 |3328GB DDR3@1866MHz |2x 400GB local SSD1x NVIDIA GM200(GeForce GTX TITAN X),12GB RAM\ |
+
+
+
diff --git a/converted/docs.it4i.cz/salomon/hardware-overview-1/uv-2000.jpeg b/converted/docs.it4i.cz/salomon/hardware-overview-1/uv-2000.jpeg
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@@ -0,0 +1,33 @@
+Introduction
+============
+
+Welcome to Salomon supercomputer cluster. The Salomon cluster consists
+of 1008 compute nodes, totaling 24192 compute cores with 129TB RAM and
+giving over 2 Pflop/s theoretical peak performance. Each node is a
+powerful x86-64 computer, equipped with 24
+cores, at least 128GB RAM. Nodes are interconnected by 7D Enhanced
+hypercube Infiniband network and equipped with Intel Xeon E5-2680v3
+processors. The Salomon cluster consists of 576 nodes without
+accelerators and 432 nodes equipped with Intel Xeon Phi MIC
+accelerators. Read more in [Hardware
+Overview](hardware-overview-1/hardware-overview.html).
+
+The cluster runs CentOS Linux [
+](http://www.bull.com/bullx-logiciels/systeme-exploitation.html)
+operating system, which is compatible with
+the RedHat [
+Linux
+family.](http://upload.wikimedia.org/wikipedia/commons/1/1b/Linux_Distribution_Timeline.svg)
+
+**Water-cooled Compute Nodes With MIC Accelerator**
+
+
+
+
+
+**Tape Library T950B**
+
+
+
+
+
diff --git a/converted/docs.it4i.cz/salomon/network-1/7D_Enhanced_hypercube.png b/converted/docs.it4i.cz/salomon/network-1/7D_Enhanced_hypercube.png
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@@ -0,0 +1,37 @@
+7D Enhanced Hypercube
+=====================
+
+[More about Job submission - Placement by IB switch / Hypercube
+dimension.](../resource-allocation-and-job-execution/job-submission-and-execution.html)
+
+Nodes may be selected via the PBS resource attribute ehc_[1-7]d .
+
+ |Hypercube|dimension|
+ --------------- |---|---|---------------------------------
+ |1D|ehc_1d|
+ |2D|ehc_2d|
+ |3D|ehc_3d|
+ |4D|ehc_4d|
+ |5D|ehc_5d|
+ |6D|ehc_6d|
+ |7D|ehc_7d|
+
+[Schematic representation of the Salomon cluster IB single-plain
+topology represents hypercube
+dimension 0](ib-single-plane-topology.html).
+
+### 7D Enhanced Hypercube {#d-enhanced-hypercube}
+
+
+
+Â
+
+ |Node type|Count|Short name|Long name|Rack|
+ -------------------------------------- - |---|---|-------- -------------------------- -------
+ |M-Cell compute nodes w/o accelerator|576|cns1 -cns576|r1i0n0 - r4i7n17|1-4|
+ |compute nodes MIC accelerated|432|cns577 - cns1008|r21u01n577 - r37u31n1008|21-38|
+
+### Â IB Topology
+
+
+
diff --git a/converted/docs.it4i.cz/salomon/network-1/IBsingleplanetopologyAcceleratednodessmall.png b/converted/docs.it4i.cz/salomon/network-1/IBsingleplanetopologyAcceleratednodessmall.png
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+IB single-plane topology
+========================
+
+
+
+A complete M-Cell assembly consists of four compute racks. Each rack
+contains 4x physical IRUs - Independent rack units. Using one dual
+socket node per one blade slot leads to 8 logical IRUs. Each rack
+contains 4x2 SGI ICE X IB Premium Blades.
+
+The SGI ICE X IB Premium Blade provides the first level of
+interconnection via dual 36-port Mellanox FDR InfiniBand ASIC switch
+with connections as follows:
+
+- 9 ports from each switch chip connect to the unified backplane, to
+ connect the 18 compute node slots
+- 3 ports on each chip provide connectivity between the chips
+- 24 ports from each switch chip connect to the external bulkhead, for
+ a total of 48
+
+###IB single-plane topology - ICEX Mcell
+
+Each colour in each physical IRU represents one dual-switch ASIC switch.
+
+
+
+Â
+
+### IB single-plane topology - Accelerated nodes
+
+Each of the 3 inter-connected D racks are equivalent to one half of
+Mcell rack. 18x D rack with MIC accelerated nodes [r21-r38] are
+equivalent to 3 Mcell racks as shown in a diagram [7D Enhanced
+Hypercube](7d-enhanced-hypercube.html).
+
+As shown in a diagram :
+
+- Racks 21, 22, 23, 24, 25, 26 are equivalent to one Mcell rack.
+- Racks 27, 28, 29, 30, 31, 32 are equivalent to one Mcell rack.
+- Racks 33, 34, 35, 36, 37, 38 are equivalent to one Mcell rack.
+
+
+
+Â
+
diff --git a/converted/docs.it4i.cz/salomon/network-1/network.md b/converted/docs.it4i.cz/salomon/network-1/network.md
new file mode 100644
index 0000000000000000000000000000000000000000..79187d02c3c1a7c5905fd4d4fb4e2939f6e19c09
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/network-1/network.md
@@ -0,0 +1,74 @@
+Network
+=======
+
+
+
+All compute and login nodes of Salomon are interconnected by 7D Enhanced
+hypercube
+[Infiniband](http://en.wikipedia.org/wiki/InfiniBand)
+network and by Gigabit
+[Ethernet](http://en.wikipedia.org/wiki/Ethernet)
+network. Only
+[Infiniband](http://en.wikipedia.org/wiki/InfiniBand)
+network may be used to transfer user data.
+
+Infiniband Network
+------------------
+
+All compute and login nodes of Salomon are interconnected by 7D Enhanced
+hypercube
+[Infiniband](http://en.wikipedia.org/wiki/InfiniBand)
+network (56 Gbps). The network topology is a [7D Enhanced
+hypercube](7d-enhanced-hypercube.html).
+
+Read more about schematic representation of the Salomon cluster [IB
+single-plain topology](ib-single-plane-topology.html)
+([hypercube dimension](7d-enhanced-hypercube.html)
+0).[>](IB%20single-plane%20topology%20-%20Accelerated%20nodes.pdf/view.html)
+
+The compute nodes may be accessed via the Infiniband network using ib0
+network interface, in address range 10.17.0.0 (mask 255.255.224.0). The
+MPI may be used to establish native Infiniband connection among the
+nodes.
+
+The network provides **2170MB/s** transfer rates via the TCP connection
+(single stream) and up to **3600MB/s** via native Infiniband protocol.
+
+Â
+
+Example
+-------
+
+`
+$ qsub -q qexp -l select=4:ncpus=16 -N Name0 ./myjob
+$ qstat -n -u username
+ Req'd Req'd Elap
+Job ID Username Queue Jobname SessID NDS TSK Memory Time S Time
+--------------- -------- -- |---|---| ------ --- --- ------ ----- - -----
+15209.isrv5 username qexp Name0 5530 4 96 -- 01:00 R 00:00
+ r4i1n0/0*24+r4i1n1/0*24+r4i1n2/0*24+r4i1n3/0*24
+`
+
+In this example, we access the node r4i1n0 by Infiniband network via the
+ib0 interface.
+
+`
+$ ssh 10.17.35.19
+`
+
+In this example, we get
+information of the Infiniband network.
+
+`
+$ ifconfig
+....
+inet addr:10.17.35.19....
+....
+
+$ ip addr show ib0
+
+....
+inet 10.17.35.19....
+....
+`
+
diff --git a/converted/docs.it4i.cz/salomon/prace.md b/converted/docs.it4i.cz/salomon/prace.md
new file mode 100644
index 0000000000000000000000000000000000000000..daee862130cdbcfc236bfec42e8ae7eab7bbb0bf
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/prace.md
@@ -0,0 +1,385 @@
+PRACE User Support
+==================
+
+
+
+Intro
+-----
+
+PRACE users coming to Salomon as to TIER-1 system offered through the
+DECI calls are in general treated as standard users and so most of the
+general documentation applies to them as well. This section shows the
+main differences for quicker orientation, but often uses references to
+the original documentation. PRACE users who don't undergo the full
+procedure (including signing the IT4I AuP on top of the PRACE AuP) will
+not have a password and thus access to some services intended for
+regular users. This can lower their comfort, but otherwise they should
+be able to use the TIER-1 system as intended. Please see the [Obtaining
+Login Credentials
+section](../get-started-with-it4innovations/obtaining-login-credentials/obtaining-login-credentials.html),
+if the same level of access is required.
+
+All general [PRACE User
+Documentation](http://www.prace-ri.eu/user-documentation/)
+should be read before continuing reading the local documentation here.
+
+[]()Help and Support
+------------------------
+
+If you have any troubles, need information, request support or want to
+install additional software, please use [PRACE
+Helpdesk](http://www.prace-ri.eu/helpdesk-guide264/).
+
+Information about the local services are provided in the [introduction
+of general user documentation](introduction.html).
+Please keep in mind, that standard PRACE accounts don't have a password
+to access the web interface of the local (IT4Innovations) request
+tracker and thus a new ticket should be created by sending an e-mail to
+support[at]it4i.cz.
+
+Obtaining Login Credentials
+---------------------------
+
+In general PRACE users already have a PRACE account setup through their
+HOMESITE (institution from their country) as a result of rewarded PRACE
+project proposal. This includes signed PRACE AuP, generated and
+registered certificates, etc.
+
+If there's a special need a PRACE user can get a standard (local)
+account at IT4Innovations. To get an account on the Salomon cluster, the
+user needs to obtain the login credentials. The procedure is the same as
+for general users of the cluster, so please see the corresponding
+[section of the general documentation
+here](../get-started-with-it4innovations/obtaining-login-credentials.html).
+
+Accessing the cluster
+---------------------
+
+### Access with GSI-SSH
+
+For all PRACE users the method for interactive access (login) and data
+transfer based on grid services from Globus Toolkit (GSI SSH and
+GridFTP) is supported.
+
+The user will need a valid certificate and to be present in the PRACE
+LDAP (please contact your HOME SITE or the primary investigator of your
+project for LDAP account creation).
+
+Most of the information needed by PRACE users accessing the Salomon
+TIER-1 system can be found here:
+
+- [General user's
+ FAQ](http://www.prace-ri.eu/Users-General-FAQs)
+- [Certificates
+ FAQ](http://www.prace-ri.eu/Certificates-FAQ)
+- [Interactive access using
+ GSISSH](http://www.prace-ri.eu/Interactive-Access-Using-gsissh)
+- [Data transfer with
+ GridFTP](http://www.prace-ri.eu/Data-Transfer-with-GridFTP-Details)
+- [Data transfer with
+ gtransfer](http://www.prace-ri.eu/Data-Transfer-with-gtransfer)
+
+Â
+
+Before you start to use any of the services don't forget to create a
+proxy certificate from your certificate:
+
+ $ grid-proxy-init
+
+To check whether your proxy certificate is still valid (by default it's
+valid 12 hours), use:
+
+ $ grid-proxy-info
+
+Â
+
+To access Salomon cluster, two login nodes running GSI SSH service are
+available. The service is available from public Internet as well as from
+the internal PRACE network (accessible only from other PRACE partners).
+
+***Access from PRACE network:**
+
+It is recommended to use the single DNS name
+salomon-prace.it4i.cz which is distributed
+between the two login nodes. If needed, user can login directly to one
+of the login nodes. The addresses are:
+
+ |Login address|Port|Protocol|Login node|
+ |---|---|
+ |salomon-prace.it4i.cz|2222|gsissh|login1, login2, login3 or login4|
+ |login1-prace.salomon.it4i.cz|2222|gsissh|login1|
+ |login2-prace.salomon.it4i.cz|2222|gsissh|login2|
+ |login3-prace.salomon.it4i.cz|2222|gsissh|login3|
+ |login4-prace.salomon.it4i.cz|2222|gsissh|login4|
+
+Â
+
+ $ gsissh -p 2222 salomon-prace.it4i.cz
+
+When logging from other PRACE system, the prace_service script can be
+used:
+
+ $ gsissh `prace_service -i -s salomon`
+
+Â
+
+***Access from public Internet:**
+
+It is recommended to use the single DNS name
+salomon.it4i.cz which is distributed between
+the two login nodes. If needed, user can login directly to one of the
+login nodes. The addresses are:
+
+ |Login address|Port|Protocol|Login node|
+ |---|---|
+ |salomon.it4i.cz|2222|gsissh|login1, login2, login3 or login4|
+ |login1.salomon.it4i.cz|2222|gsissh|login1|
+ |login2-prace.salomon.it4i.cz|2222|gsissh|login2|
+ |login3-prace.salomon.it4i.cz|2222|gsissh|login3|
+ |login4-prace.salomon.it4i.cz|2222|gsissh|login4|
+
+ $ gsissh -p 2222 salomon.it4i.cz
+
+When logging from other PRACE system, the
+prace_service script can be used:
+
+ $ gsissh `prace_service -e -s salomon`
+
+Â
+
+Although the preferred and recommended file transfer mechanism is [using
+GridFTP](prace.html#file-transfers), the GSI SSH
+implementation on Salomon supports also SCP, so for small files transfer
+gsiscp can be used:
+
+ $ gsiscp -P 2222 _LOCAL_PATH_TO_YOUR_FILE_ salomon.it4i.cz:_SALOMON_PATH_TO_YOUR_FILE_
+
+ $ gsiscp -P 2222 salomon.it4i.cz:_SALOMON_PATH_TO_YOUR_FILE_ _LOCAL_PATH_TO_YOUR_FILE_
+
+ $ gsiscp -P 2222 _LOCAL_PATH_TO_YOUR_FILE_ salomon-prace.it4i.cz:_SALOMON_PATH_TO_YOUR_FILE_
+
+ $ gsiscp -P 2222 salomon-prace.it4i.cz:_SALOMON_PATH_TO_YOUR_FILE_ _LOCAL_PATH_TO_YOUR_FILE_
+
+### Access to X11 applications (VNC)
+
+If the user needs to run X11 based graphical application and does not
+have a X11 server, the applications can be run using VNC service. If the
+user is using regular SSH based access, please see the [section in
+general
+documentation](../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html).
+
+If the user uses GSI SSH based access, then the procedure is similar to
+the SSH based access ([look
+here](../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html)),
+only the port forwarding must be done using GSI SSH:
+
+ $ gsissh -p 2222 salomon.it4i.cz -L 5961:localhost:5961
+
+### Access with SSH
+
+After successful obtainment of login credentials for the local
+IT4Innovations account, the PRACE users can access the cluster as
+regular users using SSH. For more information please see the [section in
+general
+documentation](accessing-the-cluster/shell-and-data-access/shell-and-data-access.html).
+
+File transfers
+------------------
+
+PRACE users can use the same transfer mechanisms as regular users (if
+they've undergone the full registration procedure). For information
+about this, please see [the section in the general
+documentation](accessing-the-cluster/shell-and-data-access/shell-and-data-access.html).
+
+Apart from the standard mechanisms, for PRACE users to transfer data
+to/from Salomon cluster, a GridFTP server running Globus Toolkit GridFTP
+service is available. The service is available from public Internet as
+well as from the internal PRACE network (accessible only from other
+PRACE partners).
+
+There's one control server and three backend servers for striping and/or
+backup in case one of them would fail.
+
+***Access from PRACE network:**
+
+ |Login address|Port|Node role|
+ |---|---|
+ |gridftp-prace.salomon.it4i.cz|2812|Front end /control server|
+ |lgw1-prace.salomon.it4i.cz|2813|Backend / data mover server|
+ |lgw2-prace.salomon.it4i.cz|2813|Backend / data mover server|
+ |lgw3-prace.salomon.it4i.cz|2813|Backend / data mover server|
+
+Copy files **to** Salomon by running the following commands on your
+local machine:
+
+ $ globus-url-copy file://_LOCAL_PATH_TO_YOUR_FILE_ gsiftp://gridftp-prace.salomon.it4i.cz:2812/home/prace/_YOUR_ACCOUNT_ON_SALOMON_/_PATH_TO_YOUR_FILE_
+
+Or by using prace_service script:
+
+ $ globus-url-copy file://_LOCAL_PATH_TO_YOUR_FILE_ gsiftp://`prace_service -i -f salomon`/home/prace/_YOUR_ACCOUNT_ON_SALOMON_/_PATH_TO_YOUR_FILE_
+
+Copy files **from** Salomon:
+
+ $ globus-url-copy gsiftp://gridftp-prace.salomon.it4i.cz:2812/home/prace/_YOUR_ACCOUNT_ON_SALOMON_/_PATH_TO_YOUR_FILE_ file://_LOCAL_PATH_TO_YOUR_FILE_
+
+Or by using prace_service script:
+
+ $ globus-url-copy gsiftp://`prace_service -i -f salomon`/home/prace/_YOUR_ACCOUNT_ON_SALOMON_/_PATH_TO_YOUR_FILE_ file://_LOCAL_PATH_TO_YOUR_FILE_
+
+Â
+
+***Access from public Internet:**
+
+ |Login address|Port|Node role|
+ |---|---|
+ |gridftp.salomon.it4i.cz|2812|Front end /control server|
+ |lgw1.salomon.it4i.cz|2813|Backend / data mover server|
+ |lgw2.salomon.it4i.cz|2813|Backend / data mover server|
+ |lgw3.salomon.it4i.cz|2813|Backend / data mover server|
+
+Copy files **to** Salomon by running the following commands on your
+local machine:
+
+ $ globus-url-copy file://_LOCAL_PATH_TO_YOUR_FILE_ gsiftp://gridftp.salomon.it4i.cz:2812/home/prace/_YOUR_ACCOUNT_ON_SALOMON_/_PATH_TO_YOUR_FILE_
+
+Or by using prace_service script:
+
+ $ globus-url-copy file://_LOCAL_PATH_TO_YOUR_FILE_ gsiftp://`prace_service -e -f salomon`/home/prace/_YOUR_ACCOUNT_ON_SALOMON_/_PATH_TO_YOUR_FILE_
+
+Copy files **from** Salomon:
+
+ $ globus-url-copy gsiftp://gridftp.salomon.it4i.cz:2812/home/prace/_YOUR_ACCOUNT_ON_SALOMON_/_PATH_TO_YOUR_FILE_ file://_LOCAL_PATH_TO_YOUR_FILE_
+
+Or by using prace_service script:
+
+ $ globus-url-copy gsiftp://`prace_service -e -f salomon`/home/prace/_YOUR_ACCOUNT_ON_SALOMON_/_PATH_TO_YOUR_FILE_ file://_LOCAL_PATH_TO_YOUR_FILE_
+
+Â
+
+Generally both shared file systems are available through GridFTP:
+
+ |File system mount point|Filesystem|Comment|
+ |---|---|
+ |/home|Lustre|Default HOME directories of users in format /home/prace/login/|
+ |/scratch|Lustre|Shared SCRATCH mounted on the whole cluster|
+
+More information about the shared file systems is available
+[here](storage.html).
+
+Please note, that for PRACE users a "prace" directory is used also on
+the SCRATCH file system.
+
+ |Data type|Default path|
+ |---|---|
+ |large project files|/scratch/work/user/prace/login/|
+ |large scratch/temporary data|/scratch/temp/|
+
+Usage of the cluster
+--------------------
+
+There are some limitations for PRACE user when using the cluster. By
+default PRACE users aren't allowed to access special queues in the PBS
+Pro to have high priority or exclusive access to some special equipment
+like accelerated nodes and high memory (fat) nodes. There may be also
+restrictions obtaining a working license for the commercial software
+installed on the cluster, mostly because of the license agreement or
+because of insufficient amount of licenses.
+
+For production runs always use scratch file systems. The available file
+systems are described [here](storage/storage.html).
+
+### Software, Modules and PRACE Common Production Environment
+
+All system wide installed software on the cluster is made available to
+the users via the modules. The information about the environment and
+modules usage is in this [section of general
+documentation](environment-and-modules.html).
+
+PRACE users can use the "prace" module to use the [PRACE Common
+Production
+Environment](http://www.prace-ri.eu/PRACE-common-production).
+
+ $ module load prace
+
+Â
+
+### Resource Allocation and Job Execution
+
+General information about the resource allocation, job queuing and job
+execution is in this [section of general
+documentation](resource-allocation-and-job-execution/introduction.html).
+
+For PRACE users, the default production run queue is "qprace". PRACE
+users can also use two other queues "qexp" and "qfree".
+
+
+ |queue|Active project|Project resources|Nodes|priority|authorization|walltime |
+
+ |---|---|
+ |**qexp** \|no|none required|32 nodes, max 8 per user|150|no|1 / 1h|
+ \
+
+ gt; 0 >1006 nodes, max 86 per job 0 no 24 / 48h> 0 >1006 nodes, max 86 per job 0 no 24 / 48h
+ \
+
+
+ |**qfree** \|yes|none required|752 nodes, max 86 per job|-1024|no|12 / 12h|
+ \
+
+
+qprace**, the PRACE \***: This queue is intended for
+normal production runs. It is required that active project with nonzero
+remaining resources is specified to enter the qprace. The queue runs
+with medium priority and no special authorization is required to use it.
+The maximum runtime in qprace is 48 hours. If the job needs longer time,
+it must use checkpoint/restart functionality.
+
+### Accounting & Quota
+
+The resources that are currently subject to accounting are the core
+hours. The core hours are accounted on the wall clock basis. The
+accounting runs whenever the computational cores are allocated or
+blocked via the PBS Pro workload manager (the qsub command), regardless
+of whether the cores are actually used for any calculation. See [example
+in the general
+documentation](resource-allocation-and-job-execution/resources-allocation-policy.html).
+
+PRACE users should check their project accounting using the [PRACE
+Accounting Tool
+(DART)](http://www.prace-ri.eu/accounting-report-tool/).
+
+Users who have undergone the full local registration procedure
+(including signing the IT4Innovations Acceptable Use Policy) and who
+have received local password may check at any time, how many core-hours
+have been consumed by themselves and their projects using the command
+"it4ifree". Please note that you need to know your user password to use
+the command and that the displayed core hours are "system core hours"
+which differ from PRACE "standardized core hours".
+
+The **it4ifree** command is a part of it4i.portal.clients package,
+located here:
+<https://pypi.python.org/pypi/it4i.portal.clients>
+
+ $ it4ifree
+ Password:
+     PID  Total Used ...by me Free
+ Â Â -------- ------- ------ -------- -------
+ Â Â OPEN-0-0 1500000 400644Â Â 225265 1099356
+ Â Â DD-13-1 Â Â 10000 2606 2606 7394
+
+Â
+
+By default file system quota is applied. To check the current status of
+the quota (separate for HOME and SCRATCH) use
+
+ $ quota
+ $ lfs quota -u USER_LOGIN /scratch
+
+If the quota is insufficient, please contact the
+[support](prace.html#help-and-support) and request an
+increase.
+
+Â
+
+Â
+
diff --git a/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/capacity-computing.md b/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/capacity-computing.md
new file mode 100644
index 0000000000000000000000000000000000000000..1282e33dae3f896100f05b4046a6c45f404ae549
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/capacity-computing.md
@@ -0,0 +1,434 @@
+Capacity computing
+==================
+
+
+
+Introduction
+------------
+
+In many cases, it is useful to submit huge (>100+) number of
+computational jobs into the PBS queue system. Huge number of (small)
+jobs is one of the most effective ways to execute embarrassingly
+parallel calculations, achieving best runtime, throughput and computer
+utilization.
+
+However, executing huge number of jobs via the PBS queue may strain the
+system. This strain may result in slow response to commands, inefficient
+scheduling and overall degradation of performance and user experience,
+for all users. For this reason, the number of jobs is **limited to 100
+per user, 1500 per job array**
+
+Please follow one of the procedures below, in case you wish to schedule
+more than >100 jobs at a time.
+
+- Use [Job arrays](capacity-computing.html#job-arrays)
+ when running huge number of
+ [multithread](capacity-computing.html#shared-jobscript-on-one-node)
+ (bound to one node only) or multinode (multithread across
+ several nodes) jobs
+- Use [GNU
+ parallel](capacity-computing.html#gnu-parallel) when
+ running single core jobs
+- Combine[GNU parallel with Job
+ arrays](capacity-computing.html#combining-job-arrays-and-gnu-parallel)Â
+ when running huge number of single core jobs
+
+Policy
+------
+
+1. A user is allowed to submit at most 100 jobs. Each job may be [a job
+ array](capacity-computing.html#job-arrays).
+2. The array size is at most 1000 subjobs.
+
+Job arrays
+--------------
+
+Huge number of jobs may be easily submitted and managed as a job array.
+
+A job array is a compact representation of many jobs, called subjobs.
+The subjobs share the same job script, and have the same values for all
+attributes and resources, with the following exceptions:
+
+- each subjob has a unique index, $PBS_ARRAY_INDEX
+- job Identifiers of subjobs only differ by their indices
+- the state of subjobs can differ (R,Q,...etc.)
+
+All subjobs within a job array have the same scheduling priority and
+schedule as independent jobs.
+Entire job array is submitted through a single qsub command and may be
+managed by qdel, qalter, qhold, qrls and qsig commands as a single job.
+
+### Shared jobscript
+
+All subjobs in job array use the very same, single jobscript. Each
+subjob runs its own instance of the jobscript. The instances execute
+different work controlled by $PBS_ARRAY_INDEX variable.
+
+Example:
+
+Assume we have 900 input files with name beginning with "file" (e. g.
+file001, ..., file900). Assume we would like to use each of these input
+files with program executable myprog.x, each as a separate job.
+
+First, we create a tasklist file (or subjobs list), listing all tasks
+(subjobs) - all input files in our example:
+
+`
+$ find . -name 'file*' > tasklist
+`
+
+Then we create jobscript:
+
+`
+#!/bin/bash
+#PBS -A PROJECT_ID
+#PBS -q qprod
+#PBS -l select=1:ncpus=24,walltime=02:00:00
+
+# change to local scratch directory
+SCR=/scratch/work/user/$USER/$PBS_JOBID
+mkdir -p $SCR ; cd $SCR || exit
+
+# get individual tasks from tasklist with index from PBS JOB ARRAY
+TASK=$(sed -n "${PBS_ARRAY_INDEX}p" $PBS_O_WORKDIR/tasklist)
+
+# copy input file and executable to scratch
+cp $PBS_O_WORKDIR/$TASK input ; cp $PBS_O_WORKDIR/myprog.x .
+
+# execute the calculation
+./myprog.x < input > output
+
+# copy output file to submit directory
+cp output $PBS_O_WORKDIR/$TASK.out
+`
+
+In this example, the submit directory holds the 900 input files,
+executable myprog.x and the jobscript file. As input for each run, we
+take the filename of input file from created tasklist file. We copy the
+input file to scratch /scratch/work/user/$USER/$PBS_JOBID, execute
+the myprog.x and copy the output file back to >the submit
+directory, under the $TASK.out name. The myprog.x runs on one
+node only and must use threads to run in parallel. Be aware, that if the
+myprog.x **is not multithreaded**, then all the **jobs are run as single
+thread programs in sequential** manner. Due to allocation of the whole
+node, the **accounted time is equal to the usage of whole node**, while
+using only 1/24 of the node!
+
+If huge number of parallel multicore (in means of multinode multithread,
+e. g. MPI enabled) jobs is needed to run, then a job array approach
+should also be used. The main difference compared to previous example
+using one node is that the local scratch should not be used (as it's not
+shared between nodes) and MPI or other technique for parallel multinode
+run has to be used properly.
+
+### Submit the job array
+
+To submit the job array, use the qsub -J command. The 900 jobs of the
+[example above](capacity-computing.html#array_example) may
+be submitted like this:
+
+`
+$ qsub -N JOBNAME -J 1-900 jobscript
+506493[].isrv5
+`
+
+In this example, we submit a job array of 900 subjobs. Each subjob will
+run on full node and is assumed to take less than 2 hours (please note
+the #PBS directives in the beginning of the jobscript file, dont'
+forget to set your valid PROJECT_ID and desired queue).
+
+Sometimes for testing purposes, you may need to submit only one-element
+array. This is not allowed by PBSPro, but there's a workaround:
+
+`
+$ qsub -N JOBNAME -J 9-10:2 jobscript
+`
+
+This will only choose the lower index (9 in this example) for
+submitting/running your job.
+
+### Manage the job array
+
+Check status of the job array by the qstat command.
+
+`
+$ qstat -a 506493[].isrv5
+
+isrv5:
+ Req'd Req'd Elap
+Job ID Username Queue Jobname SessID NDS TSK Memory Time S Time
+--------------- -------- -- |---|---| ------ --- --- ------ ----- - -----
+12345[].dm2 user2 qprod xx 13516 1 24 -- 00:50 B 00:02
+`
+
+The status B means that some subjobs are already running.
+
+Check status of the first 100 subjobs by the qstat command.
+
+`
+$ qstat -a 12345[1-100].isrv5
+
+isrv5:
+ Req'd Req'd Elap
+Job ID Username Queue Jobname SessID NDS TSK Memory Time S Time
+--------------- -------- -- |---|---| ------ --- --- ------ ----- - -----
+12345[1].isrv5 user2 qprod xx 13516 1 24 -- 00:50 R 00:02
+12345[2].isrv5 user2 qprod xx 13516 1 24 -- 00:50 R 00:02
+12345[3].isrv5 user2 qprod xx 13516 1 24 -- 00:50 R 00:01
+12345[4].isrv5 user2 qprod xx 13516 1 24 -- 00:50 Q --
+ . . . . . . . . . . .
+ , . . . . . . . . . .
+12345[100].isrv5 user2 qprod xx 13516 1 24 -- 00:50 Q --
+`
+
+Delete the entire job array. Running subjobs will be killed, queueing
+subjobs will be deleted.
+
+`
+$ qdel 12345[].isrv5
+`
+
+Deleting large job arrays may take a while.
+
+Display status information for all user's jobs, job arrays, and subjobs.
+
+`
+$ qstat -u $USER -t
+`
+
+Display status information for all user's subjobs.
+
+`
+$ qstat -u $USER -tJ
+`
+
+Read more on job arrays in the [PBSPro Users
+guide](../../pbspro-documentation.html).
+
+GNU parallel
+----------------
+
+Use GNU parallel to run many single core tasks on one node.
+
+GNU parallel is a shell tool for executing jobs in parallel using one or
+more computers. A job can be a single command or a small script that has
+to be run for each of the lines in the input. GNU parallel is most
+useful in running single core jobs via the queue system on Anselm.
+
+For more information and examples see the parallel man page:
+
+`
+$ module add parallel
+$ man parallel
+`
+
+### GNU parallel jobscript
+
+The GNU parallel shell executes multiple instances of the jobscript
+using all cores on the node. The instances execute different work,
+controlled by the $PARALLEL_SEQ variable.
+
+Example:
+
+Assume we have 101 input files with name beginning with "file" (e. g.
+file001, ..., file101). Assume we would like to use each of these input
+files with program executable myprog.x, each as a separate single core
+job. We call these single core jobs tasks.
+
+First, we create a tasklist file, listing all tasks - all input files in
+our example:
+
+`
+$ find . -name 'file*' > tasklist
+`
+
+Then we create jobscript:
+
+`
+#!/bin/bash
+#PBS -A PROJECT_ID
+#PBS -q qprod
+#PBS -l select=1:ncpus=24,walltime=02:00:00
+
+[ -z "$PARALLEL_SEQ" ] &&
+{ module add parallel ; exec parallel -a $PBS_O_WORKDIR/tasklist $0 ; }
+
+# change to local scratch directory
+SCR=/scratch/work/user/$USER/$PBS_JOBID/$PARALLEL_SEQ
+mkdir -p $SCR ; cd $SCR || exit
+
+# get individual task from tasklist
+TASK=$1 Â
+
+# copy input file and executable to scratch
+cp $PBS_O_WORKDIR/$TASK input
+
+# execute the calculation
+cat input > output
+
+# copy output file to submit directory
+cp output $PBS_O_WORKDIR/$TASK.out
+`
+
+In this example, tasks from tasklist are executed via the GNU
+parallel. The jobscript executes multiple instances of itself in
+parallel, on all cores of the node. Once an instace of jobscript is
+finished, new instance starts until all entries in tasklist are
+processed. Currently processed entry of the joblist may be retrieved via
+$1 variable. Variable $TASK expands to one of the input filenames from
+tasklist. We copy the input file to local scratch, execute the myprog.x
+and copy the output file back to the submit directory, under the
+$TASK.out name.Â
+
+### Submit the job
+
+To submit the job, use the qsub command. The 101 tasks' job of the
+[example above](capacity-computing.html#gp_example) may be
+submitted like this:
+
+`
+$ qsub -N JOBNAME jobscript
+12345.dm2
+`
+
+In this example, we submit a job of 101 tasks. 24 input files will be
+processed in parallel. The 101 tasks on 24 cores are assumed to
+complete in less than 2 hours.
+
+Please note the #PBS directives in the beginning of the jobscript file,
+dont' forget to set your valid PROJECT_ID and desired queue.
+
+Job arrays and GNU parallel
+-------------------------------
+
+Combine the Job arrays and GNU parallel for best throughput of single
+core jobs
+
+While job arrays are able to utilize all available computational nodes,
+the GNU parallel can be used to efficiently run multiple single-core
+jobs on single node. The two approaches may be combined to utilize all
+available (current and future) resources to execute single core jobs.
+
+Every subjob in an array runs GNU parallel to utilize all cores on the
+node
+
+### GNU parallel, shared jobscript
+
+Combined approach, very similar to job arrays, can be taken. Job array
+is submitted to the queuing system. The subjobs run GNU parallel. The
+GNU parallel shell executes multiple instances of the jobscript using
+all cores on the node. The instances execute different work, controlled
+by the $PBS_JOB_ARRAY and $PARALLEL_SEQ variables.
+
+Example:
+
+Assume we have 992 input files with name beginning with "file" (e. g.
+file001, ..., file992). Assume we would like to use each of these input
+files with program executable myprog.x, each as a separate single core
+job. We call these single core jobs tasks.
+
+First, we create a tasklist file, listing all tasks - all input files in
+our example:
+
+`
+$ find . -name 'file*' > tasklist
+`
+
+Next we create a file, controlling how many tasks will be executed in
+one subjob
+
+`
+$ seq 32 > numtasks
+`
+
+Then we create jobscript:
+
+`
+#!/bin/bash
+#PBS -A PROJECT_ID
+#PBS -q qprod
+#PBS -l select=1:ncpus=24,walltime=02:00:00
+
+[ -z "$PARALLEL_SEQ" ] &&
+{ module add parallel ; exec parallel -a $PBS_O_WORKDIR/numtasks $0 ; }
+
+# change to local scratch directory
+SCR=/scratch/work/user/$USER/$PBS_JOBID/$PARALLEL_SEQ
+mkdir -p $SCR ; cd $SCR || exit
+
+# get individual task from tasklist with index from PBS JOB ARRAY and index form Parallel
+IDX=$(($PBS_ARRAY_INDEX + $PARALLEL_SEQ - 1))
+TASK=$(sed -n "${IDX}p" $PBS_O_WORKDIR/tasklist)
+[ -z "$TASK" ] && exit
+
+# copy input file and executable to scratch
+cp $PBS_O_WORKDIR/$TASK input
+
+# execute the calculation
+cat input > output
+
+# copy output file to submit directory
+cp output $PBS_O_WORKDIR/$TASK.out
+`
+
+In this example, the jobscript executes in multiple instances in
+parallel, on all cores of a computing node. Variable $TASK expands to
+one of the input filenames from tasklist. We copy the input file to
+local scratch, execute the myprog.x and copy the output file back to the
+submit directory, under the $TASK.out name. The numtasks file controls
+how many tasks will be run per subjob. Once an task is finished, new
+task starts, until the number of tasks in numtasks file is reached.
+
+Select subjob walltime and number of tasks per subjob carefully
+
+Â When deciding this values, think about following guiding rules :
+
+1. Let n=N/24. Inequality (n+1) * T < W should hold. The N is
+ number of tasks per subjob, T is expected single task walltime and W
+ is subjob walltime. Short subjob walltime improves scheduling and
+ job throughput.
+2. Number of tasks should be modulo 24.
+3. These rules are valid only when all tasks have similar task
+ walltimes T.
+
+### Submit the job array
+
+To submit the job array, use the qsub -J command. The 992 tasks' job of
+the [example
+above](capacity-computing.html#combined_example) may be
+submitted like this:
+
+`
+$ qsub -N JOBNAME -J 1-992:32 jobscript
+12345[].dm2
+`
+
+In this example, we submit a job array of 31 subjobs. Note the -J
+1-992:**48**, this must be the same as the number sent to numtasks file.
+Each subjob will run on full node and process 24 input files in
+parallel, 48 in total per subjob. Every subjob is assumed to complete
+in less than 2 hours.
+
+Please note the #PBS directives in the beginning of the jobscript file,
+dont' forget to set your valid PROJECT_ID and desired queue.
+
+Examples
+--------
+
+Download the examples in
+[capacity.zip](capacity-computing-example),Â
+illustrating the above listed ways to run huge number of jobs. We
+recommend to try out the examples, before using this for running
+production jobs.
+
+Unzip the archive in an empty directory on Anselm and follow the
+instructions in the README file
+
+`
+$ unzip capacity.zip
+$ cd capacity
+$ cat README
+`
+
+Â
+
diff --git a/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/fairshare_formula.png b/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/fairshare_formula.png
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diff --git a/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/introduction.md b/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/introduction.md
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+Resource Allocation and Job Execution
+=====================================
+
+
+
+To run a [job](job-submission-and-execution.html),
+[computational
+resources](resources-allocation-policy.html) for this
+particular job must be allocated. This is done via the PBS Pro job
+workload manager software, which efficiently distributes workloads
+across the supercomputer. Extensive informations about PBS Pro can be
+found in the [official documentation
+here](../../pbspro-documentation.html), especially in
+the [PBS Pro User's
+Guide](https://docs.it4i.cz/pbspro-documentation/pbspro-users-guide).
+
+Resources Allocation Policy
+---------------------------
+
+The resources are allocated to the job in a fairshare fashion, subject
+to constraints set by the queue and resources available to the Project.
+[The Fairshare](job-priority.html) at Salomon ensures
+that individual users may consume approximately equal amount of
+resources per week. The resources are accessible via several queues for
+queueing the jobs. The queues provide prioritized and exclusive access
+to the computational resources. Following queues are available to Anselm
+users:
+
+- **qexp**, the \
+- **qprod**, the \***
+- **qlong**, the Long queue
+- **qmpp**, the Massively parallel queue
+- **qfat**, the queue to access SMP UV2000 machine
+- **qfree,** the Free resource utilization queue
+
+Check the queue status at <https://extranet.it4i.cz/rsweb/salomon/>
+
+Read more on the [Resource Allocation
+Policy](resources-allocation-policy.html) page.
+
+Job submission and execution
+----------------------------
+
+Use the **qsub** command to submit your jobs.
+
+The qsub submits the job into the queue. The qsub command creates a
+request to the PBS Job manager for allocation of specified resources.Â
+The **smallest allocation unit is entire node, 24 cores**, with
+exception of the qexp queue. The resources will be allocated when
+available, subject to allocation policies and constraints. **After the
+resources are allocated the jobscript or interactive shell is executed
+on first of the allocated nodes.**
+
+Read more on the [Job submission and
+execution](job-submission-and-execution.html) page.
+
diff --git a/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/job-priority.md b/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/job-priority.md
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@@ -0,0 +1,109 @@
+Job scheduling
+==============
+
+Job execution priority
+----------------------
+
+Scheduler gives each job an execution priority and then uses this job
+execution priority to select which job(s) to run.
+
+Job execution priority is determined by these job properties (in order
+of importance):
+
+1. queue priority
+2. fairshare priority
+3. eligible time
+
+### Queue priority
+
+Queue priority is priority of queue where job is queued before
+execution.
+
+Queue priority has the biggest impact on job execution priority.
+Execution priority of jobs in higher priority queues is always greater
+than execution priority of jobs in lower priority queues. Other
+properties of job used for determining job execution priority (fairshare
+priority, eligible time) cannot compete with queue priority.
+
+Queue priorities can be seen at
+<https://extranet.it4i.cz/rsweb/salomon/queues>
+
+### Fairshare priority
+
+Fairshare priority is priority calculated on recent usage of resources.
+Fairshare priority is calculated per project, all members of project
+share same fairshare priority. Projects with higher recent usage have
+lower fairshare priority than projects with lower or none recent usage.
+
+Fairshare priority is used for ranking jobs with equal queue priority.
+
+Fairshare priority is calculated as
+
+
+
+where MAX_FAIRSHARE has value 1E6,
+usage~Project~ is cumulated usage by all members of selected project,
+usage~Total~ is total usage by all users, by all projects.
+
+Usage counts allocated corehours (ncpus*walltime). Usage is decayed, or
+cut in half periodically, at the interval 168 hours (one week).
+Jobs queued in queue qexp are not calculated to project's usage.
+
+Calculated usage and fairshare priority can be seen at
+<https://extranet.it4i.cz/rsweb/salomon/projects>.
+
+Calculated fairshare priority can be also seen as
+Resource_List.fairshare attribute of a job.
+
+###Eligible time
+
+Eligible time is amount (in seconds) of eligible time job accrued while
+waiting to run. Jobs with higher eligible time gains higher
+priority.
+
+Eligible time has the least impact on execution priority. Eligible time
+is used for sorting jobs with equal queue priority and fairshare
+priority. It is very, very difficult for >eligible time to
+compete with fairshare priority.
+
+Eligible time can be seen as eligible_time attribute of
+job.
+
+### Formula
+
+Job execution priority (job sort formula) is calculated as:
+
+
+
+### Job backfilling
+
+The scheduler uses job backfilling.
+
+Backfilling means fitting smaller jobs around the higher-priority jobs
+that the scheduler is going to run next, in such a way that the
+higher-priority jobs are not delayed. Backfilling allows us to keep
+resources from becoming idle when the top job (job with the highest
+execution priority) cannot run.
+
+The scheduler makes a list of jobs to run in order of execution
+priority. Scheduler looks for smaller jobs that can fit into the usage
+gaps
+around the highest-priority jobs in the list. The scheduler looks in the
+prioritized list of jobs and chooses the highest-priority smaller jobs
+that fit. Filler jobs are run only if they will not delay the start time
+of top jobs.
+
+It means, that jobs with lower execution priority can be run before jobs
+with higher execution priority.
+
+It is **very beneficial to specify the walltime** when submitting jobs.
+
+Specifying more accurate walltime enables better schedulling, better
+execution times and better resource usage. Jobs with suitable (small)
+walltime could be backfilled - and overtake job(s) with higher priority.
+
+### Job placement
+
+Job [placement can be controlled by flags during
+submission](job-submission-and-execution.html#job_placement).
+
diff --git a/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/job-submission-and-execution.md b/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/job-submission-and-execution.md
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+Job submission and execution
+============================
+
+
+
+Job Submission
+--------------
+
+When allocating computational resources for the job, please specify
+
+1. suitable queue for your job (default is qprod)
+2. number of computational nodes required
+3. number of cores per node required
+4. maximum wall time allocated to your calculation, note that jobs
+ exceeding maximum wall time will be killed
+5. Project ID
+6. Jobscript or interactive switch
+
+Use the **qsub** command to submit your job to a queue for allocation of
+the computational resources.
+
+Submit the job using the qsub command:
+
+`
+$ qsub -A Project_ID -q queue -l select=x:ncpus=y,walltime=[[hh:]mm:]ss[.ms] jobscript
+`
+
+The qsub submits the job into the queue, in another words the qsub
+command creates a request to the PBS Job manager for allocation of
+specified resources. The resources will be allocated when available,
+subject to above described policies and constraints. **After the
+resources are allocated the jobscript or interactive shell is executed
+on first of the allocated nodes.**
+
+PBS statement nodes (qsub -l nodes=nodespec) is not supported on Salomon
+cluster.**
+
+### Job Submission Examples
+
+`
+$ qsub -A OPEN-0-0 -q qprod -l select=64:ncpus=24,walltime=03:00:00 ./myjob
+`
+
+In this example, we allocate 64 nodes, 24 cores per node, for 3 hours.
+We allocate these resources via the qprod queue, consumed resources will
+be accounted to the Project identified by Project ID OPEN-0-0. Jobscript
+myjob will be executed on the first node in the allocation.
+
+Â
+
+`
+$ qsub -q qexp -l select=4:ncpus=24 -I
+`
+
+In this example, we allocate 4 nodes, 24 cores per node, for 1 hour. We
+allocate these resources via the qexp queue. The resources will be
+available interactively
+
+Â
+
+`
+$ qsub -A OPEN-0-0 -q qlong -l select=10:ncpus=24 ./myjob
+`
+
+In this example, we allocate 10 nodes, 24 cores per node, for 72 hours.
+We allocate these resources via the qlong queue. Jobscript myjob will be
+executed on the first node in the allocation.
+
+Â
+
+`
+$ qsub -A OPEN-0-0 -q qfree -l select=10:ncpus=24 ./myjob
+`
+
+In this example, we allocate 10Â nodes, 24 cores per node, for 12 hours.
+We allocate these resources via the qfree queue. It is not required that
+the project OPEN-0-0 has any available resources left. Consumed
+resources are still accounted for. Jobscript myjob will be executed on
+the first node in the allocation.
+
+### Intel Xeon Phi co-processors
+
+To allocate a node with Xeon Phi co-processor, user needs to specify
+that in select statement. Currently only allocation of whole nodes with
+both Phi cards as the smallest chunk is supported. Standard PBSPro
+approach through attributes "accelerator", "naccelerators" and
+"accelerator_model" is used. The "accelerator_model" can be omitted,
+since on Salomon only one type of accelerator type/model is available.
+
+The absence of specialized queue for accessing the nodes with cards
+means, that the Phi cards can be utilized in any queue, including qexp
+for testing/experiments, qlong for longer jobs, qfree after the project
+resources have been spent, etc. The Phi cards are thus also available to
+PRACE users. There's no need to ask for permission to utilize the Phi
+cards in project proposals.
+
+`
+$ qsub -A OPEN-0-0 -I -q qprod -l select=1:ncpus=24:accelerator=True:naccelerators=2:accelerator_model=phi7120 ./myjob
+`
+
+In this example, we allocate 1 node, with 24 cores, with 2 Xeon Phi
+7120p cards, running batch job ./myjob. The default time for qprod is
+used, e. g. 24 hours.
+
+`
+$ qsub -A OPEN-0-0 -I -q qlong -l select=4:ncpus=24:accelerator=True:naccelerators=2 -l walltime=56:00:00 -I
+`
+
+In this example, we allocate 4 nodes, with 24 cores per node (totalling
+96 cores), with 2 Xeon Phi 7120p cards per node (totalling 8 Phi cards),
+running interactive job for 56 hours. The accelerator model name was
+omitted.
+
+### UV2000 SMP
+
+14 NUMA nodes available on UV2000
+Per NUMA node allocation.
+Jobs are isolated by cpusets.
+
+The UV2000 (node uv1) offers 3328GB of RAM and 112 cores, distributed in
+14 NUMA nodes. A NUMA node packs 8 cores and approx. 236GB RAM. In the
+PBSÂ the UV2000 provides 14 chunks, a chunk per NUMA node (seeÂ
+[Resource allocation
+policy](resources-allocation-policy.html)). The jobs on
+UV2000 are isolated from each other by cpusets, so that a job by one
+user may not utilize CPU or memory allocated to a job by other user.
+Always, full chunks are allocated, a job may only use resources of the
+NUMA nodes allocated to itself.
+
+`
+Â $ qsub -A OPEN-0-0 -q qfat -l select=14 ./myjob
+`
+
+In this example, we allocate all 14 NUMA nodes (corresponds to 14
+chunks), 112 cores of the SGI UV2000 node for 72 hours. Jobscript myjob
+will be executed on the node uv1.
+
+`
+$ qsub -A OPEN-0-0 -q qfat -l select=1:mem=2000GB ./myjob
+`
+
+In this example, we allocate 2000GB of memory on the UV2000 for 72
+hours. By requesting 2000GB of memory, 10 chunks are allocated.
+Jobscript myjob will be executed on the node uv1.
+
+### Useful tricks
+
+All qsub options may be [saved directly into the
+jobscript](job-submission-and-execution.html#PBSsaved). In
+such a case, no options to qsub are needed.
+
+`
+$ qsub ./myjob
+`
+
+Â
+
+By default, the PBS batch system sends an e-mail only when the job is
+aborted. Disabling mail events completely can be done like this:
+
+`
+$ qsub -m n
+`
+
+Advanced job placement
+--------------------------
+
+### Placement by name
+
+Specific nodes may be allocated via the PBS
+
+`
+qsub -A OPEN-0-0 -q qprod -l select=1:ncpus=24:host=r24u35n680+1:ncpus=24:host=r24u36n681 -I
+`
+
+Or using short names
+
+`
+qsub -A OPEN-0-0 -q qprod -l select=1:ncpus=24:host=cns680+1:ncpus=24:host=cns681 -I
+`
+
+In this example, we allocate nodes r24u35n680 and r24u36n681, all 24
+cores per node, for 24 hours. Consumed resources will be accounted to
+the Project identified by Project ID OPEN-0-0. The resources will be
+available interactively.
+
+### Placement by |Hypercube|dimension|
+
+Nodes may be selected via the PBS resource attribute ehc_[1-7]d .
+
+ |Hypercube|dimension|
+ --------------- |---|---|---------------------------------
+ |1D|ehc_1d|
+ |2D|ehc_2d|
+ |3D|ehc_3d|
+ |4D|ehc_4d|
+ |5D|ehc_5d|
+ |6D|ehc_6d|
+ |7D|ehc_7d|
+
+Â
+
+`
+$ qsub -A OPEN-0-0 -q qprod -l select=4:ncpus=24 -l place=group=ehc_1d -I
+`
+
+In this example, we allocate 4 nodes, 24 cores, selecting only the nodes
+with [hypercube
+dimension](../network-1/7d-enhanced-hypercube.html) 1.
+
+### Placement by IB switch
+
+Groups of computational nodes are connected to chassis integrated
+Infiniband switches. These switches form the leaf switch layer of the
+[Infiniband network](../network-1.html) . Nodes sharing
+the leaf switch can communicate most efficiently. Sharing the same
+switch prevents hops in the network and provides for unbiased, most
+efficient network communication.
+
+There are at most 9 nodes sharing the same Infiniband switch.
+
+Infiniband switch list:
+
+`
+$ qmgr -c "print node @a" | grep switch
+set node r4i1n11 resources_available.switch = r4i1s0sw1
+set node r2i0n0 resources_available.switch = r2i0s0sw1
+set node r2i0n1 resources_available.switch = r2i0s0sw1
+...
+`
+
+List of all nodes per Infiniband switch:
+
+`
+$ qmgr -c "print node @a" | grep r36sw3
+set node r36u31n964 resources_available.switch = r36sw3
+set node r36u32n965 resources_available.switch = r36sw3
+set node r36u33n966 resources_available.switch = r36sw3
+set node r36u34n967 resources_available.switch = r36sw3
+set node r36u35n968 resources_available.switch = r36sw3
+set node r36u36n969 resources_available.switch = r36sw3
+set node r37u32n970 resources_available.switch = r36sw3
+set node r37u33n971 resources_available.switch = r36sw3
+set node r37u34n972 resources_available.switch = r36sw3
+`
+
+Nodes sharing the same switch may be selected via the PBS resource
+attribute switch.
+
+We recommend allocating compute nodes of a single switch when best
+possible computational network performance is required to run the job
+efficiently:
+
+`
+$ qsub -A OPEN-0-0 -q qprod -l select=9:ncpus=24:switch=r4i1s0sw1 ./myjob
+`
+
+In this example, we request all the 9 nodes sharing the r4i1s0sw1 switch
+for 24 hours.
+
+`
+$ qsub -A OPEN-0-0 -q qprod -l select=9:ncpus=24 -l place=group=switch ./myjob
+`
+
+In this example, we request 9 nodes placed on the same switch using node
+grouping placement for 24 hours.
+
+HTML commented section #1 (turbo boost is to be implemented)
+
+Job Management
+--------------
+
+Check status of your jobs using the **qstat** and **check-pbs-jobs**
+commands
+
+`
+$ qstat -a
+$ qstat -a -u username
+$ qstat -an -u username
+$ qstat -f 12345.isrv5
+`
+
+Example:
+
+`
+$ qstat -a
+
+srv11:
+ Req'd Req'd Elap
+Job ID Username Queue Jobname SessID NDS TSK Memory Time S Time
+--------------- -------- -- |---|---| ------ --- --- ------ ----- - -----
+16287.isrv5 user1 qlong job1 6183 4 64 -- 144:0 R 38:25
+16468.isrv5 user1 qlong job2 8060 4 64 -- 144:0 R 17:44
+16547.isrv5 user2 qprod job3x 13516 2 32 -- 48:00 R 00:58
+`
+
+In this example user1 and user2 are running jobs named job1, job2 and
+job3x. The jobs job1 and job2 are using 4 nodes, 16 cores per node each.
+The job1 already runs for 38 hours and 25 minutes, job2 for 17 hours 44
+minutes. The job1 already consumed 64*38.41 = 2458.6 core hours. The
+job3x already consumed 0.96*32 = 30.93 core hours. These consumed core
+hours will be accounted on the respective project accounts, regardless
+of whether the allocated cores were actually used for computations.
+
+Check status of your jobs using check-pbs-jobs command. Check presence
+of user's PBS jobs' processes on execution hosts. Display load,
+processes. Display job standard and error output. Continuously display
+(tail -f) job standard or error output.
+
+`
+$ check-pbs-jobs --check-all
+$ check-pbs-jobs --print-load --print-processes
+$ check-pbs-jobs --print-job-out --print-job-err
+$ check-pbs-jobs --jobid JOBID --check-all --print-all
+$ check-pbs-jobs --jobid JOBID --tailf-job-out
+`
+
+Examples:
+
+`
+$ check-pbs-jobs --check-all
+JOB 35141.dm2, session_id 71995, user user2, nodes r3i6n2,r3i6n3
+Check session id: OK
+Check processes
+r3i6n2: OK
+r3i6n3: No process
+`
+
+In this example we see that job 35141.dm2 currently runs no process on
+allocated node r3i6n2, which may indicate an execution error.
+
+`
+$ check-pbs-jobs --print-load --print-processes
+JOB 35141.dm2, session_id 71995, user user2, nodes r3i6n2,r3i6n3
+Print load
+r3i6n2: LOAD: 16.01, 16.01, 16.00
+r3i6n3: LOAD: 0.01, 0.00, 0.01
+Print processes
+ %CPU CMD
+r3i6n2: 0.0 -bash
+r3i6n2: 0.0 /bin/bash /var/spool/PBS/mom_priv/jobs/35141.dm2.SC
+r3i6n2: 99.7 run-task
+...
+`
+
+In this example we see that job 35141.dm2 currently runs process
+run-task on node r3i6n2, using one thread only, while node r3i6n3 is
+empty, which may indicate an execution error.
+
+`
+$ check-pbs-jobs --jobid 35141.dm2 --print-job-out
+JOB 35141.dm2, session_id 71995, user user2, nodes r3i6n2,r3i6n3
+Print job standard output:
+======================== Job start ==========================
+Started at   : Fri Aug 30 02:47:53 CEST 2013
+Script name  : script
+Run loop 1
+Run loop 2
+Run loop 3
+`
+
+In this example, we see actual output (some iteration loops) of the job
+35141.dm2
+
+Manage your queued or running jobs, using the **qhold**, **qrls**,
+qdel,** **qsig** or **qalter** commands
+
+You may release your allocation at any time, using qdel command
+
+`
+$ qdel 12345.isrv5
+`
+
+You may kill a running job by force, using qsig command
+
+`
+$ qsig -s 9 12345.isrv5
+`
+
+Learn more by reading the pbs man page
+
+`
+$ man pbs_professional
+`
+
+Job Execution
+-------------
+
+### Jobscript
+
+Prepare the jobscript to run batch jobs in the PBS queue system
+
+The Jobscript is a user made script, controlling sequence of commands
+for executing the calculation. It is often written in bash, other
+scripts may be used as well. The jobscript is supplied to PBS **qsub**
+command as an argument and executed by the PBS Professional workload
+manager.
+
+The jobscript or interactive shell is executed on first of the allocated
+nodes.
+
+`
+$ qsub -q qexp -l select=4:ncpus=24 -N Name0 ./myjob
+$ qstat -n -u username
+
+isrv5:
+ Req'd Req'd Elap
+Job ID Username Queue Jobname SessID NDS TSK Memory Time S Time
+--------------- -------- -- |---|---| ------ --- --- ------ ----- - -----
+15209.isrv5 username qexp Name0 5530 4 96 -- 01:00 R 00:00
+ r21u01n577/0*24+r21u02n578/0*24+r21u03n579/0*24+r21u04n580/0*24
+`
+
+ In this example, the nodes r21u01n577, r21u02n578, r21u03n579,
+r21u04n580 were allocated for 1 hour via the qexp queue. The jobscript
+myjob will be executed on the node r21u01n577, while the
+nodes r21u02n578, r21u03n579, r21u04n580 are available for use as well.
+
+The jobscript or interactive shell is by default executed in home
+directory
+
+`
+$ qsub -q qexp -l select=4:ncpus=24 -I
+qsub: waiting for job 15210.isrv5 to start
+qsub: job 15210.isrv5 ready
+
+$ pwd
+/home/username
+`
+
+In this example, 4 nodes were allocated interactively for 1 hour via the
+qexp queue. The interactive shell is executed in the home directory.
+
+All nodes within the allocation may be accessed via ssh. Unallocated
+nodes are not accessible to user.
+
+The allocated nodes are accessible via ssh from login nodes. The nodes
+may access each other via ssh as well.
+
+Calculations on allocated nodes may be executed remotely via the MPI,
+ssh, pdsh or clush. You may find out which nodes belong to the
+allocation by reading the $PBS_NODEFILE file
+
+`
+qsub -q qexp -l select=2:ncpus=24 -I
+qsub: waiting for job 15210.isrv5 to start
+qsub: job 15210.isrv5 ready
+
+$ pwd
+/home/username
+
+$ sort -u $PBS_NODEFILE
+r2i5n6.ib0.smc.salomon.it4i.cz
+r4i6n13.ib0.smc.salomon.it4i.cz
+r4i7n0.ib0.smc.salomon.it4i.cz
+r4i7n2.ib0.smc.salomon.it4i.cz
+
+
+$ pdsh -w r2i5n6,r4i6n13,r4i7n[0,2] hostname
+r4i6n13: r4i6n13
+r2i5n6: r2i5n6
+r4i7n2: r4i7n2
+r4i7n0: r4i7n0
+`
+
+In this example, the hostname program is executed via pdsh from the
+interactive shell. The execution runs on all four allocated nodes. The
+same result would be achieved if the pdsh is called from any of the
+allocated nodes or from the login nodes.
+
+### Example Jobscript for MPI Calculation
+
+Production jobs must use the /scratch directory for I/O
+
+The recommended way to run production jobs is to change to /scratch
+directory early in the jobscript, copy all inputs to /scratch, execute
+the calculations and copy outputs to home directory.
+
+`
+#!/bin/bash
+
+# change to scratch directory, exit on failure
+SCRDIR=/scratch/work/user/$USER/myjob
+mkdir -p $SCRDIR
+cd $SCRDIR || exit
+
+# copy input file to scratch
+cp $PBS_O_WORKDIR/input .
+cp $PBS_O_WORKDIR/mympiprog.x .
+
+# load the mpi module
+module load OpenMPI
+
+# execute the calculation
+mpiexec -pernode ./mympiprog.x
+
+# copy output file to home
+cp output $PBS_O_WORKDIR/.
+
+#exit
+exit
+`
+
+In this example, some directory on the /home holds the input file input
+and executable mympiprog.x . We create a directory myjob on the /scratch
+filesystem, copy input and executable files from the /home directory
+where the qsub was invoked ($PBS_O_WORKDIR) to /scratch, execute the
+MPI programm mympiprog.x and copy the output file back to the /home
+directory. The mympiprog.x is executed as one process per node, on all
+allocated nodes.
+
+Consider preloading inputs and executables onto [shared
+scratch](../storage.html) before the calculation starts.
+
+In some cases, it may be impractical to copy the inputs to scratch and
+outputs to home. This is especially true when very large input and
+output files are expected, or when the files should be reused by a
+subsequent calculation. In such a case, it is users responsibility to
+preload the input files on shared /scratch before the job submission and
+retrieve the outputs manually, after all calculations are finished.
+
+Store the qsub options within the jobscript.
+Use **mpiprocs** and **ompthreads** qsub options to control the MPI job
+execution.
+
+Example jobscript for an MPI job with preloaded inputs and executables,
+options for qsub are stored within the script :
+
+`
+#!/bin/bash
+#PBS -q qprod
+#PBS -N MYJOB
+#PBS -l select=100:ncpus=24:mpiprocs=1:ompthreads=24
+#PBS -A OPEN-0-0
+
+# change to scratch directory, exit on failure
+SCRDIR=/scratch/work/user/$USER/myjob
+cd $SCRDIR || exit
+
+# load the mpi module
+module load OpenMPI
+
+# execute the calculation
+mpiexec ./mympiprog.x
+
+#exit
+exit
+`
+
+In this example, input and executable files are assumed preloaded
+manually in /scratch/$USER/myjob directory. Note the **mpiprocs** and
+ompthreads** qsub options, controlling behavior of the MPI execution.
+The mympiprog.x is executed as one process per node, on all 100
+allocated nodes. If mympiprog.x implements OpenMP threads, it will run
+24 threads per node.
+
+HTML commented section #2 (examples need to be reworked)
+
+### Example Jobscript for Single Node Calculation
+
+Local scratch directory is often useful for single node jobs. Local
+scratch will be deleted immediately after the job ends.
+Be very careful, use of RAM disk filesystem is at the expense of
+operational memory.
+
+Example jobscript for single node calculation, using [local
+scratch](../storage.html) on the node:
+
+`
+#!/bin/bash
+
+# change to local scratch directory
+cd /lscratch/$PBS_JOBID || exit
+
+# copy input file to scratch
+cp $PBS_O_WORKDIR/input .
+cp $PBS_O_WORKDIR/myprog.x .
+
+# execute the calculation
+./myprog.x
+
+# copy output file to home
+cp output $PBS_O_WORKDIR/.
+
+#exit
+exit
+`
+
+In this example, some directory on the home holds the input file input
+and executable myprog.x . We copy input and executable files from the
+home directory where the qsub was invoked ($PBS_O_WORKDIR) to local
+scratch /lscratch/$PBS_JOBID, execute the myprog.x and copy the output
+file back to the /home directory. The myprog.x runs on one node only and
+may use threads.
+
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diff --git a/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/resources-allocation-policy.md b/converted/docs.it4i.cz/salomon/resource-allocation-and-job-execution/resources-allocation-policy.md
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+Resources Allocation Policy
+===========================
+
+
+
+Resources Allocation Policy
+---------------------------
+
+The resources are allocated to the job in a fairshare fashion, subject
+to constraints set by the queue and resources available to the Project.
+The Fairshare at Anselm ensures that individual users may consume
+approximately equal amount of resources per week. Detailed information
+in the [Job scheduling](job-priority.html) section. The
+resources are accessible via several queues for queueing the jobs. The
+queues provide prioritized and exclusive access to the computational
+resources. Following table provides the queue partitioning overview:
+
+Â
+
+ |queue |active project |project resources |nodes<th align="left">min ncpus*<th align="left">priority<th align="left">authorization<th align="left">walltime |
+ | --- | --- |
+ |<strong>qexp</strong>\ |no |none required |32 nodes, max 8 per user |24 |>150 |no |1 / 1h |
+ |<strong>qprod</strong>\ |yes |> 0 |>1006 nodes, max 86 per job\ |24 |0 |no |24 / 48h |
+ |<strong>qlong</strong>Long queue |yes |> 0 |256 nodes, max 40 per job, only non-accelerated nodes allowed |24 |0 |no |72 / 144h |
+ |<strong>qmpp</strong>Massive parallel queue |yes |> 0 |1006 nodes |24 |0 |yes |2 / 4h |
+ |<strong>qfat</strong>UV2000 queue |yes |> 0\ |1 (uv1) |8 |0 |yes |24 / 48h |
+ |<strong>qfree</strong>\ |yes |none required |752 nodes, max 86 per job |24 |-1024 |no |12 / 12h |
+ |<strong><strong>qviz</strong></strong>Visualization queue |yes |none required |2 (with NVIDIA Quadro K5000) |4 |150 |no |1 / 2h |
+
+Â
+
+The qfree queue is not free of charge**. [Normal
+accounting](resources-allocation-policy.html#resources-accounting-policy)
+applies. However, it allows for utilization of free resources, once a
+Project exhausted all its allocated computational resources. This does
+not apply for Directors Discreation's projects (DD projects) by default.
+Usage of qfree after exhaustion of DD projects computational resources
+is allowed after request for this queue.
+
+Â
+
+- **qexp**, the \: This queue is dedicated for testing and
+ running very small jobs. It is not required to specify a project to
+ enter the qexp. >*>There are 2 nodes always reserved for
+ this queue (w/o accelerator), maximum 8 nodes are available via the
+ qexp for a particular user. *The nodes may be
+ allocated on per core basis. No special authorization is required to
+ use it. The maximum runtime in qexp is 1 hour.
+- **qprod**, the \***: This queue is intended for
+ normal production runs. It is required that active project with
+ nonzero remaining resources is specified to enter the qprod. All
+ nodes may be accessed via the qprod queue, however only 86 per job.
+ ** Full nodes, 24 cores per node are allocated. The queue runs with
+ medium priority and no special authorization is required to use it.
+ The maximum runtime in qprod is 48 hours.
+- **qlong**, the Long queue***: This queue is intended for long
+ production runs. It is required that active project with nonzero
+ remaining resources is specified to enter the qlong. Only 336 nodes
+ without acceleration may be accessed via the qlong queue. Full
+ nodes, 24 cores per node are allocated. The queue runs with medium
+ priority and no special authorization is required to use it.>
+ *The maximum runtime in qlong is 144 hours (three times of the
+ standard qprod time - 3 * 48 h)*
+- >***qmpp**, the massively parallel queue. This queue is
+ intended for massively parallel runs. It is required that active
+ project with nonzero remaining resources is specified to enter
+ the qmpp. All nodes may be accessed via the qmpp queue. ** Full
+ nodes, 24 cores per node are allocated. The queue runs with medium
+ priority and no special authorization is required to use it. The
+ maximum runtime in qmpp is 4 hours. An PI> *needs explicitly*
+ ask [support](https://support.it4i.cz/rt/)
+ for authorization to enter the queue for all users associated to
+ her/his Project.
+
+- >***qfat**, the UV2000 queue. This queue is dedicated
+ to access the fat SGI UV2000 SMP machine. The machine (uv1) has 112
+ Intel IvyBridge cores at 3.3GHz and 3.25TB RAM. An PI> *needs
+ explicitly* ask
+ [support](https://support.it4i.cz/rt/) for
+ authorization to enter the queue for all users associated to her/his
+ Project.***
+- **qfree**, the \***: The queue qfree is intended
+ for utilization of free resources, after a Project exhausted all its
+ allocated computational resources (Does not apply to DD projects
+ by default. DD projects have to request for persmission on qfree
+ after exhaustion of computational resources.). It is required that
+ active project is specified to enter the queue, however no remaining
+ resources are required. Consumed resources will be accounted to
+ the Project. Only 178 nodes without accelerator may be accessed from
+ this queue. Full nodes, 24 cores per node are allocated. The queue
+ runs with very low priority and no special authorization is required
+ to use it. The maximum runtime in qfree is 12 hours.
+- **qviz**, the Visualization queue***: Intended for
+ pre-/post-processing using OpenGL accelerated graphics. Currently
+ when accessing the node, each user gets 4 cores of a CPU allocated,
+ thus approximately 73 GB of RAM and 1/7 of the GPU capacity
+ (default "chunk"). *If more GPU power or RAM is required, it is
+ recommended to allocate more chunks (with 4 cores each) up to one
+ whole node per user, so that all 28 cores, 512 GB RAM and whole GPU
+ is exclusive. This is currently also the maximum allowed allocation
+ per one user. One hour of work is allocated by default, the user may
+ ask for 2 hours maximum.*
+
+Â
+
+To access node with Xeon Phi co-processor user needs to specify that in
+[job submission select
+statement](job-submission-and-execution.html).
+
+### Notes
+
+The job wall clock time defaults to **half the maximum time**, see table
+above. Longer wall time limits can be [set manually, see
+examples](job-submission-and-execution.html).
+
+Jobs that exceed the reserved wall clock time (Req'd Time) get killed
+automatically. Wall clock time limit can be changed for queuing jobs
+(state Q) using the qalter command, however can not be changed for a
+running job (state R).
+
+Salomon users may check current queue configuration at
+<https://extranet.it4i.cz/rsweb/salomon/queues>.
+
+### Queue status
+
+Check the status of jobs, queues and compute nodes at
+[https://extranet.it4i.cz/rsweb/salomon/](https://extranet.it4i.cz/rsweb/salomon)
+
+Â
+
+
+
+Â
+
+Display the queue status on Salomon:
+
+`
+$ qstat -q
+`
+
+The PBS allocation overview may be obtained also using the rspbs
+command.
+
+`
+$ rspbs
+Usage: rspbs [options]
+
+Options:
+ --version            show program's version number and exit
+ -h, --help           show this help message and exit
+ --get-server-details Print server
+ --get-queues         Print queues
+ --get-queues-details Print queues details
+ --get-reservations   Print reservations
+Â --get-reservations-details
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print reservations details
+ --get-nodes          Print nodes of PBS complex
+ --get-nodeset        Print nodeset of PBS complex
+ --get-nodes-details  Print nodes details
+ --get-jobs           Print jobs
+ --get-jobs-details   Print jobs details
+Â --get-jobs-check-params
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print jobid, job state, session_id, user, nodes
+ --get-users          Print users of jobs
+Â --get-allocated-nodes
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print allocated nodes of jobs
+Â --get-allocated-nodeset
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print allocated nodeset of jobs
+ --get-node-users     Print node users
+ --get-node-jobs      Print node jobs
+ --get-node-ncpus     Print number of ncpus per node
+Â --get-node-allocated-ncpus
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print number of allocated ncpus per node
+ --get-node-qlist     Print node qlist
+ --get-node-ibswitch  Print node ibswitch
+ --get-user-nodes     Print user nodes
+ --get-user-nodeset   Print user nodeset
+ --get-user-jobs      Print user jobs
+ --get-user-jobc      Print number of jobs per user
+ --get-user-nodec     Print number of allocated nodes per user
+ --get-user-ncpus     Print number of allocated ncpus per user
+ --get-qlist-nodes    Print qlist nodes
+ --get-qlist-nodeset  Print qlist nodeset
+ --get-ibswitch-nodes Print ibswitch nodes
+Â --get-ibswitch-nodeset
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Print ibswitch nodeset
+ --summary            Print summary
+Â --get-node-ncpu-chart
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Obsolete. Print chart of allocated ncpus per node
+Â --server=SERVERÂ Â Â Â Â Â Use given PBS server
+Â --state=STATEÂ Â Â Â Â Â Â Â Only for given job state
+Â --jobid=JOBIDÂ Â Â Â Â Â Â Â Only for given job ID
+Â --user=USERÂ Â Â Â Â Â Â Â Â Â Only for given user
+Â --node=NODEÂ Â Â Â Â Â Â Â Â Â Only for given node
+Â --nodestate=NODESTATE
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Only for given node state (affects only --get-node*
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â --get-qlist-* --get-ibswitch-* actions)
+ --incl-finished      Include finished jobs
+`
+
+Resources Accounting Policy
+-------------------------------
+
+### The Core-Hour
+
+The resources that are currently subject to accounting are the
+core-hours. The core-hours are accounted on the wall clock basis. The
+accounting runs whenever the computational cores are allocated or
+blocked via the PBS Pro workload manager (the qsub command), regardless
+of whether the cores are actually used for any calculation. 1 core-hour
+is defined as 1 processor core allocated for 1 hour of wall clock time.
+Allocating a full node (24 cores) for 1 hour accounts to 24 core-hours.
+See example in the [Job submission and
+execution](job-submission-and-execution.html) section.
+
+### Check consumed resources
+
+The **it4ifree** command is a part of it4i.portal.clients package,
+located here:
+<https://pypi.python.org/pypi/it4i.portal.clients>
+
+User may check at any time, how many core-hours have been consumed by
+himself/herself and his/her projects. The command is available on
+clusters' login nodes.
+
+`
+$ it4ifree
+Password:
+    PID  Total Used ...by me Free
+Â Â -------- ------- ------ -------- -------
+Â Â OPEN-0-0 1500000 400644Â Â 225265 1099356
+Â Â DD-13-1 Â Â 10000 2606 2606 7394
+`
+
+Â
+
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diff --git a/converted/docs.it4i.cz/salomon/software/ansys/ansys-cfx.md b/converted/docs.it4i.cz/salomon/software/ansys/ansys-cfx.md
new file mode 100644
index 0000000000000000000000000000000000000000..39777fa74cf823baa4e4d062eff1d37394b24d4b
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/ansys/ansys-cfx.md
@@ -0,0 +1,87 @@
+ANSYS CFX
+=========
+
+[ANSYS
+CFX](http://www.ansys.com/Products/Simulation+Technology/Fluid+Dynamics/Fluid+Dynamics+Products/ANSYS+CFX)
+software is a high-performance, general purpose fluid dynamics program
+that has been applied to solve wide-ranging fluid flow problems for over
+20 years. At the heart of ANSYS CFX is its advanced solver technology,
+the key to achieving reliable and accurate solutions quickly and
+robustly. The modern, highly parallelized solver is the foundation for
+an abundant choice of physical models to capture virtually any type of
+phenomena related to fluid flow. The solver and its many physical models
+are wrapped in a modern, intuitive, and flexible GUI and user
+environment, with extensive capabilities for customization and
+automation using session files, scripting and a powerful expression
+language.
+
+To run ANSYS CFX in batch mode you can utilize/modify the default
+cfx.pbs script and execute it via the qsub command.
+
+ #!/bin/bash
+ #PBS -l nodes=2:ppn=24
+ #PBS -q qprod
+ #PBS -N $USER-CFX-Project
+ #PBS -A OPEN-0-0
+
+ #! Mail to user when job terminate or abort
+ #PBS -m ae
+
+ #!change the working directory (default is home directory)
+ #cd <working directory> (working directory must exists)
+ WORK_DIR="/scratch/work/user/$USER"
+ cd $WORK_DIR
+
+ echo Running on host `hostname`
+ echo Time is `date`
+ echo Directory is `pwd`
+ echo This jobs runs on the following processors:
+ echo `cat $PBS_NODEFILE`
+
+ module load ANSYS
+
+ #### Set number of processors per host listing
+ procs_per_host=24
+ #### Create host list
+ hl=""
+ for host in `cat $PBS_NODEFILE`
+ do
+ if [ "$hl" = "" ]
+ then hl="$host:$procs_per_host"
+ else hl="${hl}:$host:$procs_per_host"
+ fi
+ done
+
+ echo Machines: $hl
+
+ # prevent ANSYS from attempting to use scif0 interface
+ export MPI_IC_ORDER="UDAPL"
+
+ #-dev input.def includes the input of CFX analysis in DEF format
+ #-P the name of prefered license feature (aa_r=ANSYS Academic Research, ane3fl=Multiphysics(commercial))
+ cfx5solve -def input.def -size 4 -size-ni 4x -part-large -start-method "Platform MPI Distributed Parallel" -par-dist $hl -P aa_r
+
+Header of the pbs file (above) is common and description can be findÂ
+[this
+site](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+SVS FEM recommends to utilize sources by keywords: nodes, ppn. These
+keywords allows to address directly the number of nodes (computers) and
+cores (ppn) which will be utilized in the job. Also the rest of code
+assumes such structure of allocated resources.
+
+Working directory has to be created before sending pbs job into the
+queue. Input file should be in working directory or full path to input
+file has to be specified. >Input file has to be defined by common
+CFX def file which is attached to the cfx solver via parameter
+-def
+
+License**Â should be selected by parameter -P (Big letter **P**).
+Licensed products are the following: aa_r
+(ANSYS **Academic Research), ane3fl (ANSYS
+Multiphysics)-**Commercial.
+[More about licensing here](licensing.html)
+
+Â We have observed that the -P settings does not always work. Please set
+your [license
+preferences](setting-license-preferences.html) instead.
+
diff --git a/converted/docs.it4i.cz/salomon/software/ansys/ansys-fluent.md b/converted/docs.it4i.cz/salomon/software/ansys/ansys-fluent.md
new file mode 100644
index 0000000000000000000000000000000000000000..bbacf3ea538d8b030f0c1504601ab9869e6dd166
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/ansys/ansys-fluent.md
@@ -0,0 +1,206 @@
+ANSYS Fluent
+============
+
+[ANSYS
+Fluent](http://www.ansys.com/Products/Simulation+Technology/Fluid+Dynamics/Fluid+Dynamics+Products/ANSYS+Fluent)
+software contains the broad physical modeling capabilities needed to
+model flow, turbulence, heat transfer, and reactions for industrial
+applications ranging from air flow over an aircraft wing to combustion
+in a furnace, from bubble columns to oil platforms, from blood flow to
+semiconductor manufacturing, and from clean room design to wastewater
+treatment plants. Special models that give the software the ability to
+model in-cylinder combustion, aeroacoustics, turbomachinery, and
+multiphase systems have served to broaden its reach.
+
+1. Common way to run Fluent over pbs file
+------------------------------------------------------
+
+To run ANSYS Fluent in batch mode you can utilize/modify the
+default fluent.pbs script and execute it via the qsub command.
+
+ #!/bin/bash
+ #PBS -S /bin/bash
+ #PBS -l nodes=2:ppn=24
+ #PBS -q qprod
+ #PBS -N Fluent-Project
+ #PBS -A OPEN-0-0
+
+ #! Mail to user when job terminate or abort
+ #PBS -m ae
+
+ #!change the working directory (default is home directory)
+ #cd <working directory> (working directory must exists)
+ WORK_DIR="/scratch/work/user/$USER"
+ cd $WORK_DIR
+
+ echo Running on host `hostname`
+ echo Time is `date`
+ echo Directory is `pwd`
+ echo This jobs runs on the following processors:
+ echo `cat $PBS_NODEFILE`
+
+ #### Load ansys module so that we find the cfx5solve command
+ module load ANSYS
+
+ # Use following line to specify MPI for message-passing instead
+ NCORES=`wc -l $PBS_NODEFILE |awk '{print $1}'`
+
+ /apps/cae/ANSYS/16.1/v161/fluent/bin/fluent 3d -t$NCORES -cnf=$PBS_NODEFILE -g -i fluent.jou
+
+Header of the pbs file (above) is common and description can be find on
+[this
+site](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+[SVS FEM](http://www.svsfem.cz) recommends to utilize
+sources by keywords: nodes, ppn. These keywords allows to address
+directly the number of nodes (computers) and cores (ppn) which will be
+utilized in the job. Also the rest of code assumes such structure of
+allocated resources.
+
+Working directory has to be created before sending pbs job into the
+queue. Input file should be in working directory or full path to input
+file has to be specified. Input file has to be defined by common Fluent
+journal file which is attached to the Fluent solver via parameter -i
+fluent.jou
+
+Journal file with definition of the input geometry and boundary
+conditions and defined process of solution has e.g. the following
+structure:
+
+ /file/read-case aircraft_2m.cas.gz
+ /solve/init
+ init
+ /solve/iterate
+ 10
+ /file/write-case-dat aircraft_2m-solution
+ /exit yes
+
+The appropriate dimension of the problem has to be set by
+parameter (2d/3d).Â
+
+2. Fast way to run Fluent from command line
+--------------------------------------------------------
+
+ fluent solver_version [FLUENT_options] -i journal_file -pbs
+
+This syntax will start the ANSYS FLUENT job under PBS Professional using
+the qsub command in a batch manner. When
+resources are available, PBS Professional will start the job and return
+a job ID, usually in the form of
+*job_ID.hostname*. This job ID can then be used
+to query, control, or stop the job using standard PBS Professional
+commands, such as qstat or
+qdel. The job will be run out of the current
+working directory, and all output will be written to the file
+fluent.o>Â
+*job_ID*. Â Â Â Â
+
+3. Running Fluent via user's config file
+----------------------------------------
+
+The sample script uses a configuration file called
+pbs_fluent.conf  if no command line arguments
+are present. This configuration file should be present in the directory
+from which the jobs are submitted (which is also the directory in which
+the jobs are executed). The following is an example of what the content
+of pbs_fluent.conf can be:
+
+`
+ input="example_small.flin"
+ case="Small-1.65m.cas"
+ fluent_args="3d -pmyrinet"
+ outfile="fluent_test.out"
+ mpp="true"
+`
+
+The following is an explanation of the parameters:
+
+ input is the name of the input
+file.
+
+ case is the name of the
+.cas file that the input file will utilize.
+
+ fluent_args are extra ANSYS FLUENT
+arguments. As shown in the previous example, you can specify the
+interconnect by using the -p interconnect
+command. The available interconnects include
+ethernet (the default),
+myrinet, class="monospace">
+infiniband, vendor,
+altix>, and
+crayx. The MPI is selected automatically, based
+on the specified interconnect.
+
+ outfile is the name of the file to which
+the standard output will be sent.
+
+ mpp="true" will tell the job script to
+execute the job across multiple processors. Â Â Â Â Â Â Â Â
+
+To run ANSYS Fluent in batch mode with user's config file you can
+utilize/modify the following script and execute it via the qsub
+command.
+
+`
+#!/bin/sh
+#PBS -l nodes=2:ppn=24
+#PBS -1 qprod
+#PBS -N Fluent-Project
+#PBS -A OPEN-0-0
+
+ cd $PBS_O_WORKDIR
+
+ #We assume that if they didn’t specify arguments then they should use the
+ #config file if [ "xx${input}${case}${mpp}${fluent_args}zz" = "xxzz" ]; then
+ if [ -f pbs_fluent.conf ]; then
+ . pbs_fluent.conf
+ else
+ printf "No command line arguments specified, "
+ printf "and no configuration file found. Exiting n"
+ fi
+ fi
+
+
+ #Augment the ANSYS FLUENT command line arguments case "$mpp" in
+ true)
+ #MPI job execution scenario
+ num_nodes=â€cat $PBS_NODEFILE | sort -u | wc -lâ€
+ cpus=â€expr $num_nodes * $NCPUSâ€
+ #Default arguments for mpp jobs, these should be changed to suit your
+ #needs.
+ fluent_args="-t${cpus} $fluent_args -cnf=$PBS_NODEFILE"
+ ;;
+ *)
+ #SMP case
+ #Default arguments for smp jobs, should be adjusted to suit your
+ #needs.
+ fluent_args="-t$NCPUS $fluent_args"
+ ;;
+ esac
+ #Default arguments for all jobs
+ fluent_args="-ssh -g -i $input $fluent_args"
+
+ echo "---------- Going to start a fluent job with the following settings:
+ Input: $input
+ Case: $case
+ Output: $outfile
+ Fluent arguments: $fluent_args"
+
+ #run the solver
+ /apps/cae/ANSYS/16.1/v161/fluent/bin/fluent $fluent_args > $outfile
+`
+
+It runs the jobs out of the directory from which they are
+submitted (PBS_O_WORKDIR).
+
+4. Running Fluent in parralel
+-----------------------------
+
+Fluent could be run in parallel only under Academic Research
+license. To do so this ANSYS Academic Research license must be placed
+before ANSYS CFD license in user preferences. To make this change
+[anslic_admin utility should be
+run](setting-license-preferences.html).
+
+Â
+
diff --git a/converted/docs.it4i.cz/salomon/software/ansys/ansys-ls-dyna.md b/converted/docs.it4i.cz/salomon/software/ansys/ansys-ls-dyna.md
new file mode 100644
index 0000000000000000000000000000000000000000..6120f49e88e3dd9187c4459573cf1f83f9053228
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/ansys/ansys-ls-dyna.md
@@ -0,0 +1,84 @@
+ANSYS LS-DYNA
+=============
+
+[ANSYS
+LS-DYNA](http://www.ansys.com/Products/Simulation+Technology/Structural+Mechanics/Explicit+Dynamics/ANSYS+LS-DYNA)
+software provides convenient and easy-to-use access to the
+technology-rich, time-tested explicit solver without the need to contend
+with the complex input requirements of this sophisticated program.
+Introduced in 1996, ANSYS LS-DYNA capabilities have helped customers in
+numerous industries to resolve highly intricate design
+issues. >ANSYS Mechanical users have been able take advantage of
+complex explicit solutions for a long time utilizing the traditional
+ANSYS Parametric Design Language (APDL) environment. >These
+explicit capabilities are available to ANSYS Workbench users as well.
+The Workbench platform is a powerful, comprehensive, easy-to-use
+environment for engineering simulation. CAD import from all sources,
+geometry cleanup, automatic meshing, solution, parametric optimization,
+result visualization and comprehensive report generation are all
+available within a single fully interactive modern graphical user
+environment.
+
+To run ANSYS LS-DYNA in batch mode you can utilize/modify the
+default ansysdyna.pbs script and execute it via the qsub command.
+
+ #!/bin/bash
+ #PBS -l nodes=2:ppn=24
+ #PBS -q qprod
+ #PBS -N DYNA-Project
+ #PBS -A OPEN-0-0
+
+ #! Mail to user when job terminate or abort
+ #PBS -m ae
+
+ #!change the working directory (default is home directory)
+ #cd <working directory>
+ WORK_DIR="/scratch/work/user/$USER"
+ cd $WORK_DIR
+
+ echo Running on host `hostname`
+ echo Time is `date`
+ echo Directory is `pwd`
+ echo This jobs runs on the following processors:
+ echo `cat $PBS_NODEFILE`
+
+ module load ANSYS
+
+ #### Set number of processors per node
+ procs_per_host=24
+ #### Create host list
+ hl=""
+ for host in `cat $PBS_NODEFILE`
+ do
+ if [ "$hl" = "" ]
+ then hl="$host:$procs_per_host"
+ else hl="${hl}:$host:$procs_per_host"
+ fi
+ done
+
+ echo Machines: $hl
+
+ # prevent ANSYS from attempting to use scif0 interface
+ export MPI_IC_ORDER="UDAPL"
+
+ lsdyna161 -dis -usessh -machines "$hl" i=input.k
+
+Header of the pbs file (above) is common and description can be
+find > on [this
+site](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+[SVS FEM](http://www.svsfem.cz) recommends to utilize
+sources by keywords: nodes, ppn. These keywords allows to address
+directly the number of nodes (computers) and cores (ppn) which will be
+utilized in the job. Also the rest of code assumes such structure of
+allocated resources.
+
+Working directory has to be created before sending pbs job into the
+queue. Input file should be in working directory or full path to input
+file has to be specified. Input file has to be defined by common LS-DYNA
+.**k** file which is attached to the ansys solver via parameter i=
+
+Without setting environment variable MPI_IC_ORDER="UDAPL", ANSYS will
+fail to run on nodes with Xeon Phi accelerator (it will use the virtual
+interface of Phi cards instead of the real InfiniBand interface and MPI
+will fail.
+
diff --git a/converted/docs.it4i.cz/salomon/software/ansys/ansys-mechanical-apdl.md b/converted/docs.it4i.cz/salomon/software/ansys/ansys-mechanical-apdl.md
new file mode 100644
index 0000000000000000000000000000000000000000..a33a8bf916a7290a08343efecbb3dd2f663a5f32
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/ansys/ansys-mechanical-apdl.md
@@ -0,0 +1,79 @@
+ANSYS MAPDL
+===========
+
+**[ANSYS
+Multiphysics](http://www.ansys.com/Products/Simulation+Technology/Structural+Mechanics/ANSYS+Multiphysics)**
+software offers a comprehensive product solution for both multiphysics
+and single-physics analysis. The product includes structural, thermal,
+fluid and both high- and low-frequency electromagnetic analysis. The
+product also contains solutions for both direct and sequentially coupled
+physics problems including direct coupled-field elements and the ANSYS
+multi-field solver.
+
+To run ANSYS MAPDL in batch mode you can utilize/modify the
+default mapdl.pbs script and execute it via the qsub command.
+
+ #!/bin/bash
+ #PBS -l nodes=2:ppn=24
+ #PBS -q qprod
+ #PBS -N ANSYS-Project
+ #PBS -A OPEN-0-0
+
+ #! Mail to user when job terminate or abort
+ #PBS -m ae
+
+ #!change the working directory (default is home directory)
+ #cd <working directory> (working directory must exists)
+ WORK_DIR="/scratch/work/user/$USER"
+ cd $WORK_DIR
+
+ echo Running on host `hostname`
+ echo Time is `date`
+ echo Directory is `pwd`
+ echo This jobs runs on the following processors:
+ echo `cat $PBS_NODEFILE`
+
+ module load ANSYS/16.1
+
+ #### Set number of processors per host listing
+ procs_per_host=24
+ #### Create host list
+ hl=""
+ for host in `cat $PBS_NODEFILE`
+ do
+ if [ "$hl" = "" ]
+ then hl="$host:$procs_per_host"
+ else hl="${hl}:$host:$procs_per_host"
+ fi
+ done
+
+ echo Machines: $hl
+
+ # prevent ANSYS from attempting to use scif0 interface
+ export MPI_IC_ORDER="UDAPL"
+
+ #-i input.dat includes the input of analysis in APDL format
+ #-o file.out is output file from ansys where all text outputs will be redirected
+ #-p the name of license feature (aa_r=ANSYS Academic Research, ane3fl=Multiphysics(commercial), aa_r_dy=Academic AUTODYN)
+ ansys161 -b -dis -usessh -p aa_r -i input.dat -o file.out -machines "$hl" -dir $WORK_DIR
+
+Header of the PBS file (above) is common and description can be find on
+[this
+site](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+[SVS FEM](http://www.svsfem.cz) recommends to utilize
+sources by keywords: nodes, ppn. These keywords allows to address
+directly the number of nodes (computers) and cores (ppn) which will be
+utilized in the job. Also the rest of code assumes such structure of
+allocated resources.
+
+Working directory has to be created before sending pbs job into the
+queue. Input file should be in working directory or full path to input
+file has to be specified. Input file has to be defined by common APDL
+file which is attached to the ansys solver via parameter -i
+
+License** should be selected by parameter -p. Licensed products are
+the following: aa_r (ANSYS **Academic Research), ane3fl (ANSYS
+Multiphysics)-**Commercial**, aa_r_dy (ANSYS **Academic
+AUTODYN)>
+[More about licensing here](licensing.html)
+
diff --git a/converted/docs.it4i.cz/salomon/software/ansys/ansys-products-mechanical-fluent-cfx-mapdl.md b/converted/docs.it4i.cz/salomon/software/ansys/ansys-products-mechanical-fluent-cfx-mapdl.md
new file mode 100644
index 0000000000000000000000000000000000000000..43dffc3a14231d9bb0e2e31dcfc09d6e3bd5f759
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/ansys/ansys-products-mechanical-fluent-cfx-mapdl.md
@@ -0,0 +1,31 @@
+Overview of ANSYS Products
+==========================
+
+[SVS FEM](http://www.svsfem.cz/)** as **[ANSYS
+Channel partner](http://www.ansys.com/)**Â for Czech
+Republic provided all ANSYS licenses for all clusters and supports of
+all ANSYS Products (Multiphysics, Mechanical, MAPDL, CFX, Fluent,
+Maxwell, LS-DYNA...) to IT staff and ANSYS users. If you are challenging
+to problem of ANSYS functionality contact
+please [hotline@svsfem.cz](mailto:hotline@svsfem.cz?subject=Ostrava%20-%20ANSELM)
+
+The clusters provides as commercial as academic variants. Academic
+variants are distinguished by "**Academic...**" word in the name of
+Â license or by two letter preposition "**aa_**" in the license feature
+name. Change of license is realized on command line respectively
+directly in user's pbs file (see individual products). [More about
+licensing here](licensing.html)
+
+To load the latest version of any ANSYS product (Mechanical, Fluent,
+CFX, MAPDL,...) load the module:
+
+ $ module load ANSYS
+
+ANSYS supports interactive regime, but due to assumed solution of
+extremely difficult tasks it is not recommended.
+
+If user needs to work in interactive regime we recommend to configure
+the RSM service on the client machine which allows to forward the
+solution to the clusters directly from the client's Workbench project
+(see ANSYS RSM service).
+
diff --git a/converted/docs.it4i.cz/salomon/software/ansys/ansys.md b/converted/docs.it4i.cz/salomon/software/ansys/ansys.md
new file mode 100644
index 0000000000000000000000000000000000000000..93f9c151da204a8a03bf3d4696f63f151ec898da
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/ansys/ansys.md
@@ -0,0 +1,31 @@
+Overview of ANSYS Products
+==========================
+
+[SVS FEM](http://www.svsfem.cz/)** as **[ANSYS
+Channel partner](http://www.ansys.com/)**Â for Czech
+Republic provided all ANSYS licenses for all clusters and supports of
+all ANSYS Products (Multiphysics, Mechanical, MAPDL, CFX, Fluent,
+Maxwell, LS-DYNA...) to IT staff and ANSYS users. If you are challenging
+to problem of ANSYS functionality contact
+please [hotline@svsfem.cz](mailto:hotline@svsfem.cz?subject=Ostrava%20-%20ANSELM)
+
+The clusters provides as commercial as academic variants. Academic
+variants are distinguished by "**Academic...**" word in the name of
+Â license or by two letter preposition "**aa_**" in the license feature
+name. Change of license is realized on command line respectively
+directly in user's pbs file (see individual products). [More about
+licensing here](ansys/licensing.html)
+
+To load the latest version of any ANSYS product (Mechanical, Fluent,
+CFX, MAPDL,...) load the module:
+
+ $ module load ANSYS
+
+ANSYS supports interactive regime, but due to assumed solution of
+extremely difficult tasks it is not recommended.
+
+If user needs to work in interactive regime we recommend to configure
+the RSM service on the client machine which allows to forward the
+solution to the clusters directly from the client's Workbench project
+(see ANSYS RSM service).
+
diff --git a/converted/docs.it4i.cz/salomon/software/ansys/licensing.md b/converted/docs.it4i.cz/salomon/software/ansys/licensing.md
new file mode 100644
index 0000000000000000000000000000000000000000..8ee4bc1c61dc30f9579e90c4c646752c25513f3d
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/ansys/licensing.md
@@ -0,0 +1,45 @@
+Licensing and Available Versions
+================================
+
+ANSYS licence can be used by:
+-----------------------------
+
+- all persons in the carrying out of the CE IT4Innovations Project (In
+ addition to the primary licensee, which is VSB - Technical
+ University of Ostrava, users are CE IT4Innovations third parties -
+ CE IT4Innovations project partners, particularly the University of
+ Ostrava, the Brno University of Technology - Faculty of Informatics,
+ the Silesian University in Opava, Institute of Geonics AS CR.)
+- all
+ persons who have a valid
+ license
+- students
+ of the Technical University
+
+ANSYS Academic Research
+-----------------------
+
+The licence intended to be used for science and research, publications,
+students’ projects (academic licence).
+
+ANSYS COM
+---------
+
+The licence intended to be used for science and research, publications,
+students’ projects, commercial research with no commercial use
+restrictions.
+
+Available Versions
+------------------
+
+- 16.1
+- 17.0
+
+License Preferences
+-------------------
+
+Please [see this page to set license
+preferences](setting-license-preferences.html).
+
+Â
+
diff --git a/converted/docs.it4i.cz/salomon/software/ansys/setting-license-preferences.md b/converted/docs.it4i.cz/salomon/software/ansys/setting-license-preferences.md
new file mode 100644
index 0000000000000000000000000000000000000000..5c6d63842d2d5b6e76f056815beebba89e8e8989
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/ansys/setting-license-preferences.md
@@ -0,0 +1,34 @@
+Setting license preferences
+===========================
+
+Some ANSYS tools allow you to explicitly specify usage of academic or
+commercial licenses in the command line (eg.Â
+ansys161 -p aa_r to select Academic Research
+license). However, we have observed that not all tools obey this option
+and choose commercial license.
+
+Thus you need to configure preferred license order with ANSLIC_ADMIN.
+Please follow these steps and move Academic Research license to the  top
+or bottom of the list accordingly.
+
+Launch the ANSLIC_ADMIN utility in a graphical environment:
+
+ $ANSYSLIC_DIR/lic_admin/anslic_admin
+
+ANSLIC_ADMIN Utility will be run
+
+
+
+
+
+
+
+Â
+
+ANSYS Academic Research license should be moved up to the top or down to
+the bottom of the list.
+
+Â
+
+
+
diff --git a/converted/docs.it4i.cz/salomon/software/ansys/workbench.md b/converted/docs.it4i.cz/salomon/software/ansys/workbench.md
new file mode 100644
index 0000000000000000000000000000000000000000..78ec8caa5d83c589a2542035fac57d0cd997b75a
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/ansys/workbench.md
@@ -0,0 +1,74 @@
+Workbench
+=========
+
+Workbench Batch Mode
+--------------------
+
+It is possible to run Workbench scripts in batch mode. You need to
+configure solvers of individual components to run in parallel mode. Open
+your project in Workbench. Then, for example, in Mechanical, go to Tools
+- Solve Process Settings ..., click Advanced button as shown on the
+screenshot.
+
+
+
+Enable Distribute Solution checkbox and enter number of cores (eg. 48 to
+run on two Salomon nodes). If you want the job to run on more then 1
+node, you must also provide a so called MPI appfile. In the Additional
+Command Line Arguments input field, enter :
+
+ -mpifile /path/to/my/job/mpifile.txt
+
+Where /path/to/my/job is the directory where your project is saved. We
+will create the file mpifile.txt programatically later in the batch
+script. For more information, refer to *ANSYS Mechanical APDL Parallel
+Processing* *Guide*.
+
+Now, save the project and close Workbench. We will use this script to
+launch the job:
+
+ #!/bin/bash
+ #PBS -l select=2:ncpus=24
+ #PBS -q qprod
+ #PBS -N test9_mpi_2
+ #PBS -A OPEN-0-0
+
+ # Mail to user when job terminate or abort
+ #PBS -m a
+
+ # change the working directory
+ WORK_DIR="$PBS_O_WORKDIR"
+ cd $WORK_DIR
+
+ echo Running on host `hostname`
+ echo Time is `date`
+ echo Directory is `pwd`
+ echo This jobs runs on the following nodes:
+ echo `cat $PBS_NODEFILE`
+
+ module load ANSYS
+
+ #### Set number of processors per host listing
+ procs_per_host=24
+ #### Create MPI appfile
+ echo -n "" > mpifile.txt
+ for host in `cat $PBS_NODEFILE`
+ do
+ echo "-h $host -np $procs_per_host $ANSYS160_DIR/bin/ansysdis161 -dis" > mpifile.txt
+ done
+
+ #-i input.dat includes the input of analysis in APDL format
+ #-o file.out is output file from ansys where all text outputs will be redirected
+ #-p the name of license feature (aa_r=ANSYS Academic Research, ane3fl=Multiphysics(commercial), aa_r_dy=Academic AUTODYN)
+
+ # prevent using scsif0 interface on accelerated nodes
+ export MPI_IC_ORDER="UDAPL"
+ # spawn remote process using SSH (default is RSH)
+ export MPI_REMSH="/usr/bin/ssh"
+
+ runwb2 -R jou6.wbjn -B -F test9.wbpj
+
+The solver settings are saved in file solvehandlers.xml, which is not
+located in the project directory. Verify your solved settings when
+uploading a project from your local computer.
+
diff --git a/converted/docs.it4i.cz/salomon/software/chemistry/molpro.md b/converted/docs.it4i.cz/salomon/software/chemistry/molpro.md
new file mode 100644
index 0000000000000000000000000000000000000000..44f8d92337f0c4f4ae4b4dd0d4e90cab4d53ce28
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/chemistry/molpro.md
@@ -0,0 +1,91 @@
+Molpro
+======
+
+Molpro is a complete system of ab initio programs for molecular
+electronic structure calculations.
+
+About Molpro
+------------
+
+Molpro is a software package used for accurate ab-initio quantum
+chemistry calculations. More information can be found at the [official
+webpage](http://www.molpro.net/).
+
+License
+-------
+
+Molpro software package is available only to users that have a valid
+license. Please contact support to enable access to Molpro if you have a
+valid license appropriate for running on our cluster (eg. >academic
+research group licence, parallel execution).
+
+To run Molpro, you need to have a valid license token present in
+" $HOME/.molpro/token". You can
+download the token from [Molpro
+website](https://www.molpro.net/licensee/?portal=licensee).
+
+Installed version
+-----------------
+
+Currently on Salomon is installed version 2010.1, patch level 57,
+parallel version compiled with Intel compilers and Intel MPI.
+
+Compilation parameters are default :
+
+ |Parameter|Value|
+ ------------------------------------------- |---|---|-------------------
+ |max number of atoms|200|
+ |max number of valence orbitals|300|
+ |max number of basis functions|4095|
+ |max number of states per symmmetry|20|
+ |max number of state symmetries|16|
+ |max number of records|200|
+ |max number of primitives|maxbfn x [2]|
+
+Â
+
+Running
+-------
+
+Molpro is compiled for parallel execution using MPI and OpenMP. By
+default, Molpro reads the number of allocated nodes from PBS and
+launches a data server on one node. On the remaining allocated nodes,
+compute processes are launched, one process per node, each with 16
+threads. You can modify this behavior by using -n, -t and helper-server
+options. Please refer to the [Molpro
+documentation](http://www.molpro.net/info/2010.1/doc/manual/node9.html)
+for more details.Â
+
+The OpenMP parallelization in Molpro is limited and has been observed to
+produce limited scaling. We therefore recommend to use MPI
+parallelization only. This can be achieved by passing option
+mpiprocs=24:ompthreads=1 to PBS.
+
+You are advised to use the -d option to point to a directory in [SCRATCH
+filesystem](../../storage.html). Molpro can produce a
+large amount of temporary data during its run, and it is important that
+these are placed in the fast scratch filesystem.
+
+### Example jobscript
+
+ #PBS -A IT4I-0-0
+ #PBS -q qprod
+ #PBS -l select=1:ncpus=24:mpiprocs=24:ompthreads=1
+
+ cd $PBS_O_WORKDIR
+
+ # load Molpro module
+ module add Molpro/2010.1-patch-57-intel2015b
+
+ # create a directory in the SCRATCH filesystem
+ mkdir -p /scratch/work/user/$USER/$PBS_JOBID
+
+ # copy an example input
+ cp /apps/all/Molpro/2010.1-patch57/molprop_2010_1_Linux_x86_64_i8/examples/caffeine_opt_diis.com .
+
+ # run Molpro with default options
+ molpro -d /scratch/work/user/$USER/$PBS_JOBID caffeine_opt_diis.com
+
+ # delete scratch directory
+ rm -rf /scratch/work/user/$USER/$PBS_JOBIDÂ
+
diff --git a/converted/docs.it4i.cz/salomon/software/chemistry/nwchem.md b/converted/docs.it4i.cz/salomon/software/chemistry/nwchem.md
new file mode 100644
index 0000000000000000000000000000000000000000..b37cb96e6ff2cfcabcfcf4e78a741e1a86e8eaf8
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/chemistry/nwchem.md
@@ -0,0 +1,66 @@
+NWChem
+======
+
+High-Performance Computational Chemistry
+
+Introduction
+-------------------------
+
+NWChem aims to provide its users with computational chemistry
+tools that are scalable both in their ability to treat large scientific
+computational chemistry problems efficiently, and in their use of
+available parallel computing resources from high-performance parallel
+supercomputers to conventional workstation clusters.
+
+[Homepage](http://www.nwchem-sw.org/index.php/Main_Page)
+
+Installed versions
+------------------
+
+The following versions are currently installed :Â
+
+- >NWChem/6.3.revision2-2013-10-17-Python-2.7.8, current release.
+ Compiled with Intel compilers, MKL and Intel MPI
+
+ Â
+
+- >NWChem/6.5.revision26243-intel-2015b-2014-09-10-Python-2.7.8
+
+For a current list of installed versions, execute :Â
+
+ module avail NWChem
+
+The recommend to use version 6.5. Version 6.3 fails on Salomon nodes
+with accelerator, because it attempts to communicate over scif0
+interface. In 6.5 this is avoided by
+setting ARMCI_OPENIB_DEVICE=mlx4_0, this setting is included in the
+module.
+
+Running
+-------
+
+NWChem is compiled for parallel MPI execution. Normal procedure for MPI
+jobs applies. Sample jobscript :
+
+ #PBS -A IT4I-0-0
+ #PBS -q qprod
+ #PBS -l select=1:ncpus=24:mpiprocs=24
+
+ cd $PBS_O_WORKDIR
+ module add NWChem/6.5.revision26243-intel-2015b-2014-09-10-Python-2.7.8
+ mpirun nwchem h2o.nw
+
+Options
+--------------------
+
+Please refer to [the
+documentation](http://www.nwchem-sw.org/index.php/Release62:Top-level)Â and
+in the input file set the following directives :
+
+- >MEMORY : controls the amount of memory NWChem will use
+- >SCRATCH_DIR : set this to a directory in [SCRATCH
+ filesystem](../../storage.html)Â (or run the
+ calculation completely in a scratch directory). For certain
+ calculations, it might be advisable to reduce I/O by forcing
+ "direct" mode, eg. "scf direct"
+
diff --git a/converted/docs.it4i.cz/salomon/software/chemistry/phono3py.md b/converted/docs.it4i.cz/salomon/software/chemistry/phono3py.md
new file mode 100644
index 0000000000000000000000000000000000000000..14148e5a9e3f53cf593765a7b697a35fc5ab2be7
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/chemistry/phono3py.md
@@ -0,0 +1,202 @@
+Phono3py
+========
+
+
+
+Â Introduction
+-------------
+
+This GPL software calculates phonon-phonon interactions via the third
+order force constants. It allows to obtain lattice thermal conductivity,
+phonon lifetime/linewidth, imaginary part of self energy at the lowest
+order, joint density of states (JDOS) and weighted-JDOS. For details see
+Phys. Rev. B 91, 094306 (2015) and
+http://atztogo.github.io/phono3py/index.html
+
+Load the phono3py/0.9.14-ictce-7.3.5-Python-2.7.9 module
+
+`
+$ module load phono3py/0.9.14-ictce-7.3.5-Python-2.7.9
+`
+
+Example of calculating thermal conductivity of Si using VASP code.
+------------------------------------------------------------------
+
+### Calculating force constants
+
+One needs to calculate second order and third order force constants
+using the diamond structure of silicon stored in
+[POSCAR](phono3py-input/poscar-si)Â (the same form as in
+VASP) using single displacement calculations within supercell.
+
+`
+$ cat POSCAR
+Â Si
+Â Â 1.0
+Â Â Â Â 5.4335600309153529Â Â Â 0.0000000000000000Â Â Â 0.0000000000000000
+Â Â Â Â 0.0000000000000000Â Â Â 5.4335600309153529Â Â Â 0.0000000000000000
+Â Â Â Â 0.0000000000000000Â Â Â 0.0000000000000000Â Â Â 5.4335600309153529
+Â Si
+Â Â 8
+Direct
+Â Â 0.8750000000000000Â 0.8750000000000000Â 0.8750000000000000
+Â Â 0.8750000000000000Â 0.3750000000000000Â 0.3750000000000000
+Â Â 0.3750000000000000Â 0.8750000000000000Â 0.3750000000000000
+Â Â 0.3750000000000000Â 0.3750000000000000Â 0.8750000000000000
+Â Â 0.1250000000000000Â 0.1250000000000000Â 0.1250000000000000
+Â Â 0.1250000000000000Â 0.6250000000000000Â 0.6250000000000000
+Â Â 0.6250000000000000Â 0.1250000000000000Â 0.6250000000000000
+Â Â 0.6250000000000000Â 0.6250000000000000Â 0.1250000000000000
+`
+
+### Generating displacement using 2x2x2 supercell for both second and third order force constants
+
+`
+$ phono3py -d --dim="2 2 2" -c POSCAR
+`
+
+ 111 displacements is created stored in
+disp_fc3.yaml, and the structure input files with this
+displacements are POSCAR-00XXX, where the XXX=111.
+
+`
+disp_fc3.yaml POSCAR-00008 POSCAR-00017 POSCAR-00026 POSCAR-00035 POSCAR-00044 POSCAR-00053 POSCAR-00062 POSCAR-00071 POSCAR-00080 POSCAR-00089 POSCAR-00098 POSCAR-00107
+POSCARÂ Â Â Â Â Â Â Â POSCAR-00009Â POSCAR-00018Â POSCAR-00027Â POSCAR-00036Â POSCAR-00045Â POSCAR-00054Â POSCAR-00063Â POSCAR-00072Â POSCAR-00081Â POSCAR-00090Â POSCAR-00099Â POSCAR-00108
+POSCAR-00001Â Â POSCAR-00010Â POSCAR-00019Â POSCAR-00028Â POSCAR-00037Â POSCAR-00046Â POSCAR-00055Â POSCAR-00064Â POSCAR-00073Â POSCAR-00082Â POSCAR-00091Â POSCAR-00100Â POSCAR-00109
+POSCAR-00002Â Â POSCAR-00011Â POSCAR-00020Â POSCAR-00029Â POSCAR-00038Â POSCAR-00047Â POSCAR-00056Â POSCAR-00065Â POSCAR-00074Â POSCAR-00083Â POSCAR-00092Â POSCAR-00101Â POSCAR-00110
+POSCAR-00003Â Â POSCAR-00012Â POSCAR-00021Â POSCAR-00030Â POSCAR-00039Â POSCAR-00048Â POSCAR-00057Â POSCAR-00066Â POSCAR-00075Â POSCAR-00084Â POSCAR-00093Â POSCAR-00102Â POSCAR-00111
+POSCAR-00004Â Â POSCAR-00013Â POSCAR-00022Â POSCAR-00031Â POSCAR-00040Â POSCAR-00049Â POSCAR-00058Â POSCAR-00067Â POSCAR-00076Â POSCAR-00085Â POSCAR-00094Â POSCAR-00103
+POSCAR-00005Â Â POSCAR-00014Â POSCAR-00023Â POSCAR-00032Â POSCAR-00041Â POSCAR-00050Â POSCAR-00059Â POSCAR-00068Â POSCAR-00077Â POSCAR-00086Â POSCAR-00095Â POSCAR-00104
+POSCAR-00006Â Â POSCAR-00015Â POSCAR-00024Â POSCAR-00033Â POSCAR-00042Â POSCAR-00051Â POSCAR-00060Â POSCAR-00069Â POSCAR-00078Â POSCAR-00087Â POSCAR-00096Â POSCAR-00105
+POSCAR-00007Â Â POSCAR-00016Â POSCAR-00025Â POSCAR-00034Â POSCAR-00043Â POSCAR-00052Â POSCAR-00061Â POSCAR-00070Â POSCAR-00079Â POSCAR-00088Â POSCAR-00097Â POSCAR-00106
+`
+
+ For each displacement the forces needs to be
+calculated, i.e. in form of the output file of VASP (vasprun.xml). For a
+single VASP calculations one needs
+[KPOINTS](phono3py-input/KPOINTS),
+[POTCAR](phono3py-input/POTCAR),
+[INCAR](phono3py-input/INCAR) in your case directory
+(where you have POSCARS) and those 111 displacements calculations can be
+generated by [prepare.sh](phono3py-input/prepare.sh)
+script. Then each of the single 111 calculations is submitted
+[run.sh](phono3py-input/run.sh) by
+[submit.sh](phono3py-input/submit.sh).
+
+`
+$./prepare.sh
+$ls
+disp-00001Â disp-00009Â disp-00017Â disp-00025Â disp-00033Â disp-00041Â disp-00049Â disp-00057Â disp-00065Â disp-00073Â disp-00081Â disp-00089Â disp-00097Â disp-00105Â Â Â Â INCAR
+disp-00002Â disp-00010Â disp-00018Â disp-00026Â disp-00034Â disp-00042Â disp-00050Â disp-00058Â disp-00066Â disp-00074Â disp-00082Â disp-00090Â disp-00098Â disp-00106Â Â Â Â KPOINTS
+disp-00003Â disp-00011Â disp-00019Â disp-00027Â disp-00035Â disp-00043Â disp-00051Â disp-00059Â disp-00067Â disp-00075Â disp-00083Â disp-00091Â disp-00099Â disp-00107Â Â Â Â POSCAR
+disp-00004Â disp-00012Â disp-00020Â disp-00028Â disp-00036Â disp-00044Â disp-00052Â disp-00060Â disp-00068Â disp-00076Â disp-00084Â disp-00092Â disp-00100Â disp-00108Â Â Â Â POTCAR
+disp-00005Â disp-00013Â disp-00021Â disp-00029Â disp-00037Â disp-00045Â disp-00053Â disp-00061Â disp-00069Â disp-00077Â disp-00085Â disp-00093Â disp-00101Â disp-00109Â Â Â Â prepare.sh
+disp-00006Â disp-00014Â disp-00022Â disp-00030Â disp-00038Â disp-00046Â disp-00054Â disp-00062Â disp-00070Â disp-00078Â disp-00086Â disp-00094Â disp-00102Â disp-00110Â Â Â Â run.sh
+disp-00007Â disp-00015Â disp-00023Â disp-00031Â disp-00039Â disp-00047Â disp-00055Â disp-00063Â disp-00071Â disp-00079Â disp-00087Â disp-00095Â disp-00103Â disp-00111Â Â Â Â submit.sh
+disp-00008Â disp-00016Â disp-00024Â disp-00032Â disp-00040Â disp-00048Â disp-00056Â disp-00064Â disp-00072Â disp-00080Â disp-00088Â disp-00096Â disp-00104Â disp_fc3.yaml
+`
+
+ Taylor your run.sh script to fit into your project and
+other needs and submit all 111 calculations using submit.sh
+script
+
+`
+$ ./submit.sh
+`
+
+ Collecting results and post-processing with phono3py
+---------------------------------------------------------------------------
+
+ Once all jobs are finished and vasprun.xml is created in
+each disp-XXXXX directory the collection is done by
+
+`
+$ phono3py --cf3 disp-{00001..00111}/vasprun.xml
+`
+
+ and
+`disp_fc2.yaml, FORCES_FC2`, `FORCES_FC3`{.docutils
+.literal} and disp_fc3.yaml should appear and put into the hdf
+format by
+
+`
+$ phono3py --dim="2 2 2" -c POSCAR
+`
+
+resulting in `fc2.hdf5` and `fc3.hdf5`{.docutils
+.literal}
+
+### Thermal conductivity
+
+ The phonon lifetime calculations takes some time,
+however is independent on grid points, so could be splitted:
+
+`
+$ phono3py --fc3 --fc2 --dim="2 2 2" --mesh="9 9 9" --sigma 0.1 --wgp
+`
+
+### Inspecting ir_grid_points.yaml
+
+`
+$ grep grid_point ir_grid_points.yaml
+num_reduced_ir_grid_points: 35
+ir_grid_points:Â # [address, weight]
+- grid_point: 0
+- grid_point: 1
+- grid_point: 2
+- grid_point: 3
+- grid_point: 4
+- grid_point: 10
+- grid_point: 11
+- grid_point: 12
+- grid_point: 13
+- grid_point: 20
+- grid_point: 21
+- grid_point: 22
+- grid_point: 30
+- grid_point: 31
+- grid_point: 40
+- grid_point: 91
+- grid_point: 92
+- grid_point: 93
+- grid_point: 94
+- grid_point: 101
+- grid_point: 102
+- grid_point: 103
+- grid_point: 111
+- grid_point: 112
+- grid_point: 121
+- grid_point: 182
+- grid_point: 183
+- grid_point: 184
+- grid_point: 192
+- grid_point: 193
+- grid_point: 202
+- grid_point: 273
+- grid_point: 274
+- grid_point: 283
+- grid_point: 364
+`
+
+one finds which grid points needed to be calculated, for instance using
+following
+
+`
+$ phono3py --fc3 --fc2 --dim="2 2 2" --mesh="9 9 9" -c POSCARÂ --sigma 0.1 --br --write-gamma --gp="0 1 2
+`
+
+ one calculates grid points 0, 1, 2. To automize one can
+use for instance scripts to submit 5 points in series, see
+[gofree-cond1.sh](phono3py-input/gofree-cond1.sh)
+
+`
+$ qsub gofree-cond1.sh
+`
+
+ Finally the thermal conductivity result is produced by
+grouping single conductivity per grid calculations usingÂ
+
+`
+$ phono3py --fc3 --fc2 --dim="2 2 2" --mesh="9 9 9" --br --read_gamma
+`
+
diff --git a/converted/docs.it4i.cz/salomon/software/compilers.md b/converted/docs.it4i.cz/salomon/software/compilers.md
new file mode 100644
index 0000000000000000000000000000000000000000..125d99238603c065fc4d9b1f7845ea442c93ebf4
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/compilers.md
@@ -0,0 +1,194 @@
+Compilers
+=========
+
+Available compilers, including GNU, INTEL and UPC compilers
+
+
+
+There are several compilers for different programming languages
+available on the cluster:
+
+- C/C++
+- Fortran 77/90/95/HPF
+- Unified Parallel C
+- Java
+
+The C/C++ and Fortran compilers are provided by:
+
+Opensource:
+
+- GNU GCC
+- Clang/LLVM
+
+Commercial licenses:
+
+- Intel
+- PGI
+
+Intel Compilers
+---------------
+
+For information about the usage of Intel Compilers and other Intel
+products, please read the [Intel Parallel
+studio](intel-suite.html) page.
+
+PGI Compilers
+-------------
+
+The Portland Group Cluster Development Kit (PGI CDK) is available.
+
+ $ module load PGI
+ $ pgcc -v
+ $ pgc++ -v
+ $ pgf77 -v
+ $ pgf90 -v
+ $ pgf95 -v
+ $ pghpf -v
+
+The PGI CDK also incudes tools for debugging and profiling.
+
+PGDBG OpenMP/MPI debugger and PGPROF OpenMP/MPI profiler are available
+
+ $ module load PGI
+ $ module load Java
+ $ pgdbg &
+ $ pgprof &
+
+For more information, see the [PGI
+page](http://www.pgroup.com/products/pgicdk.htm).
+
+GNU
+---
+
+For compatibility reasons there are still available the original (old
+4.4.7-11) versions of GNU compilers as part of the OS. These are
+accessible in the search path by default.
+
+It is strongly recommended to use the up to date version which comes
+with the module GCC:
+
+ $ module load GCC
+ $ gcc -v
+ $ g++ -v
+ $ gfortran -v
+
+With the module loaded two environment variables are predefined. One for
+maximum optimizations on the cluster's architecture, and the other for
+debugging purposes:
+
+ $ echo $OPTFLAGS
+ -O3 -march=native
+
+ $ echo $DEBUGFLAGS
+ -O0 -g
+
+For more information about the possibilities of the compilers, please
+see the man pages.
+
+Unified Parallel C
+------------------
+
+UPC is supported by two compiler/runtime implementations:
+
+- GNU - SMP/multi-threading support only
+- Berkley - multi-node support as well as SMP/multi-threading support
+
+### GNU UPC Compiler
+
+To use the GNU UPC compiler and run the compiled binaries use the module
+gupc
+
+ $ module add gupc
+ $ gupc -v
+ $ g++ -v
+
+Simple program to test the compiler
+
+ $ cat count.upc
+
+ /* hello.upc - a simple UPC example */
+ #include <upc.h>
+ #include <stdio.h>
+
+ int main() {
+ Â if (MYTHREAD == 0) {
+ Â Â Â printf("Welcome to GNU UPC!!!n");
+ Â }
+ Â upc_barrier;
+ Â printf(" - Hello from thread %in", MYTHREAD);
+ Â return 0;
+ }
+
+To compile the example use
+
+ $ gupc -o count.upc.x count.upc
+
+To run the example with 5 threads issue
+
+ $ ./count.upc.x -fupc-threads-5
+
+For more informations see the man pages.
+
+### Berkley UPC Compiler
+
+To use the Berkley UPC compiler and runtime environment to run the
+binaries use the module bupc
+
+ $ module add BerkeleyUPC/2.16.2-gompi-2015b
+ $ upcc -version
+
+As default UPC network the "smp" is used. This is very quick and easy
+way for testing/debugging, but limited to one node only.
+
+For production runs, it is recommended to use the native Infiband
+implementation of UPC network "ibv". For testing/debugging using
+multiple nodes, the "mpi" UPC network is recommended. Please note, that
+the selection of the network is done at the compile time** and not at
+runtime (as expected)!
+
+Example UPC code:
+
+ $ cat hello.upc
+
+ /* hello.upc - a simple UPC example */
+ #include <upc.h>
+ #include <stdio.h>
+
+ int main() {
+ Â if (MYTHREAD == 0) {
+ Â Â Â printf("Welcome to Berkeley UPC!!!n");
+ Â }
+ Â upc_barrier;
+ Â printf(" - Hello from thread %in", MYTHREAD);
+ Â return 0;
+ }
+
+To compile the example with the "ibv" UPC network use
+
+ $ upcc -network=ibv -o hello.upc.x hello.upc
+
+To run the example with 5 threads issue
+
+ $ upcrun -n 5 ./hello.upc.x
+
+To run the example on two compute nodes using all 48 cores, with 48
+threads, issue
+
+ $ qsub -I -q qprod -A PROJECT_ID -l select=2:ncpus=24
+ $ module add bupc
+ $ upcrun -n 48 ./hello.upc.x
+
+Â For more informations see the man pages.
+
+Java
+----
+
+For information how to use Java (runtime and/or compiler), please read
+the [Java page](java.html).
+
+nVidia CUDA
+
+For information how to work with nVidia CUDA, please read the [nVidia
+CUDA
+page](../../anselm-cluster-documentation/software/nvidia-cuda.html).
+
diff --git a/converted/docs.it4i.cz/salomon/software/comsol/comsol-multiphysics.md b/converted/docs.it4i.cz/salomon/software/comsol/comsol-multiphysics.md
new file mode 100644
index 0000000000000000000000000000000000000000..5948a933f5fc8c928e5c34e481359a1fa446601f
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/comsol/comsol-multiphysics.md
@@ -0,0 +1,204 @@
+COMSOL Multiphysics®
+====================
+
+
+
+Introduction
+
+-------------------------
+
+[COMSOL](http://www.comsol.com)
+is a powerful environment for modelling and solving various engineering
+and scientific problems based on partial differential equations. COMSOL
+is designed to solve coupled or multiphysics phenomena. For many
+standard engineering problems COMSOL provides add-on products such as
+electrical, mechanical, fluid flow, and chemical
+applications.
+
+- >[Structural Mechanics
+ Module](http://www.comsol.com/structural-mechanics-module),
+
+
+- >[Heat Transfer
+ Module](http://www.comsol.com/heat-transfer-module),
+
+
+- >[CFD
+ Module](http://www.comsol.com/cfd-module),
+
+
+- >[Acoustics
+ Module](http://www.comsol.com/acoustics-module),
+
+
+- >and [many
+ others](http://www.comsol.com/products)
+
+COMSOL also allows an
+interface support for
+equation-based modelling of
+partial differential
+equations.
+
+Execution
+
+----------------------
+
+On the clusters COMSOL is available in the latest stable
+version. There are two variants of the release:
+
+- >**Non commercial** or so
+ called >**EDU
+ variant**>, which can be used for research
+ and educational purposes.
+
+- >**Commercial** or so called
+ >**COM variant**,
+ which can used also for commercial activities.
+ >**COM variant**
+ has only subset of features compared to the
+ >**EDU
+ variant**> available.
+
+ More about
+ licensing will be posted here
+ soon.
+
+
+To load the of COMSOL load the module
+
+`
+$ module load COMSOL/51-EDU
+`
+
+By default the **EDU
+variant**> will be loaded. If user needs other
+version or variant, load the particular version. To obtain the list of
+available versions use
+
+`
+$ module avail COMSOL
+`
+
+If user needs to prepare COMSOL jobs in the interactive mode
+it is recommend to use COMSOL on the compute nodes via PBS Pro
+scheduler. In order run the COMSOL Desktop GUI on Windows is recommended
+to use the [Virtual Network Computing
+(VNC)](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html).
+
+`
+$ xhost +
+$ qsub -I -X -A PROJECT_ID -q qprod -l select=1:ppn=24
+$ module load COMSOL
+$ comsol
+`
+
+To run COMSOL in batch mode, without the COMSOL Desktop GUI
+environment, user can utilized the default (comsol.pbs) job script and
+execute it via the qsub command.
+
+`
+#!/bin/bash
+#PBS -l select=3:ppn=24
+#PBS -q qprod
+#PBS -N JOB_NAME
+#PBS -AÂ PROJECT_ID
+
+cd /scratch/work/user/$USER/ || exit
+
+echo Time is `date`
+echo Directory is `pwd`
+echo '**PBS_NODEFILE***START*******'
+cat $PBS_NODEFILE
+echo '**PBS_NODEFILE***END*********'
+
+text_nodes < cat $PBS_NODEFILE
+
+module load COMSOL
+# module load COMSOL/51-EDU
+
+ntask=$(wc -l $PBS_NODEFILE)
+
+comsol -nn ${ntask} batch -configuration /tmp –mpiarg –rmk –mpiarg pbs -tmpdir /scratch/$USER/ -inputfile name_input_f.mph -outputfile name_output_f.mph -batchlog name_log_f.log
+`
+
+Working directory has to be created before sending the
+(comsol.pbs) job script into the queue. Input file (name_input_f.mph)
+has to be in working directory or full path to input file has to be
+specified. The appropriate path to the temp directory of the job has to
+be set by command option (-tmpdir).
+
+LiveLink™* *for MATLAB®^
+-------------------------
+
+COMSOL is the software package for the numerical solution of
+the partial differential equations. LiveLink for MATLAB allows
+connection to the
+COMSOL>><span><span><span><span>**®**</span>^
+API (Application Programming Interface) with the benefits of the
+programming language and computing environment of the MATLAB.
+
+LiveLink for MATLAB is available in both
+**EDU** and
+**COM**
+**variant** of the
+COMSOL release. On the clusters 1 commercial
+(>**COM**) license
+and the 5 educational
+(>**EDU**) licenses
+of LiveLink for MATLAB (please see the [ISV
+Licenses](../isv_licenses.html)) are available.
+Following example shows how to start COMSOL model from MATLAB via
+LiveLink in the interactive mode.
+
+`
+$ xhost +
+$ qsub -I -X -A PROJECT_ID -q qexp -l select=1:ppn=24
+$ module load MATLAB
+$ module load COMSOL
+$ comsol server MATLAB
+`
+
+At the first time to launch the LiveLink for MATLAB
+(client-MATLAB/server-COMSOL connection) the login and password is
+requested and this information is not requested again.
+
+To run LiveLink for MATLAB in batch mode with
+(comsol_matlab.pbs) job script you can utilize/modify the following
+script and execute it via the qsub command.
+
+`
+#!/bin/bash
+#PBS -l select=3:ppn=24
+#PBS -q qprod
+#PBS -N JOB_NAME
+#PBS -AÂ PROJECT_ID
+
+cd /scratch/work/user/$USER || exit
+
+echo Time is `date`
+echo Directory is `pwd`
+echo '**PBS_NODEFILE***START*******'
+cat $PBS_NODEFILE
+echo '**PBS_NODEFILE***END*********'
+
+text_nodes < cat $PBS_NODEFILE
+
+module load MATLAB
+module load COMSOL/51-EDU
+
+ntask=$(wc -l $PBS_NODEFILE)
+
+comsol -nn ${ntask} server -configuration /tmp -mpiarg -rmk -mpiarg pbs -tmpdir /scratch/work/user/$USER/work &
+cd /apps/cae/COMSOL/51/mli
+matlab -nodesktop -nosplash -r "mphstart; addpath /scratch/work/user/$USER/work; test_job"
+`
+
+This example shows how to run Livelink for MATLAB with following
+configuration: 3 nodes and 16 cores per node. Working directory has to
+be created before submitting (comsol_matlab.pbs) job script into the
+queue. Input file (test_job.m) has to be in working directory or full
+path to input file has to be specified. The Matlab command option (-r
+”mphstart”) created a connection with a COMSOL server using the default
+port number.
+
diff --git a/converted/docs.it4i.cz/salomon/software/comsol/licensing-and-available-versions.md b/converted/docs.it4i.cz/salomon/software/comsol/licensing-and-available-versions.md
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index 0000000000000000000000000000000000000000..ffafbd5d118af4ba88750cfc5ac284e0a536d501
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/comsol/licensing-and-available-versions.md
@@ -0,0 +1,40 @@
+Licensing and Available Versions
+================================
+
+Comsol licence can be used by:
+------------------------------
+
+- all persons in the carrying out of the CE IT4Innovations Project (In
+ addition to the primary licensee, which is VSB - Technical
+ University of Ostrava, users are CE IT4Innovations third parties -
+ CE IT4Innovations project partners, particularly the University of
+ Ostrava, the Brno University of Technology - Faculty of Informatics,
+ the Silesian University in Opava, Institute of Geonics AS CR.)
+- all
+ persons who have a valid
+ license
+- students
+ of the Technical University
+
+Comsol EDU Network Licence
+--------------------------
+
+The licence intended to be used for science and research, publications,
+students’ projects, teaching (academic licence).
+
+Comsol COM Network Licence
+--------------------------
+
+The licence intended to be used for science and research, publications,
+students’ projects, commercial research with no commercial use
+restrictions. > E
+nables the solution
+of at least one job
+by one user in one
+program start.
+
+Available Versions
+------------------
+
+- ver. 51
+
diff --git a/converted/docs.it4i.cz/salomon/software/debuggers.md b/converted/docs.it4i.cz/salomon/software/debuggers.md
new file mode 100644
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--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/debuggers.md
@@ -0,0 +1,90 @@
+Debuggers and profilers summary
+===============================
+
+
+
+Introduction
+------------
+
+We provide state of the art programms and tools to develop, profile and
+debug HPC codes at IT4Innovations.
+On these pages, we provide an overview of the profiling and debugging
+tools available on Anslem at IT4I.
+
+Intel debugger
+--------------
+
+Intel debugger is no longer available since Parallel Studio version 2015
+
+The intel debugger version 13.0 is available, via module intel. The
+debugger works for applications compiled with C and C++ compiler and the
+ifort fortran 77/90/95 compiler. The debugger provides java GUI
+environment. Use [X
+display](../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html)
+for running the GUI.
+
+ $ module load intel
+ $ idb
+
+Read more at the [Intel
+Debugger](intel-suite/intel-debugger.html) page.
+
+Allinea Forge (DDT/MAP)
+-----------------------
+
+Allinea DDT, is a commercial debugger primarily for debugging parallel
+MPI or OpenMP programs. It also has a support for GPU (CUDA) and Intel
+Xeon Phi accelerators. DDT provides all the standard debugging features
+(stack trace, breakpoints, watches, view variables, threads etc.) for
+every thread running as part of your program, or for every process -
+even if these processes are distributed across a cluster using an MPI
+implementation.
+
+ $ module load Forge
+ $ forge
+
+Read more at the [Allinea
+DDT](debuggers/allinea-ddt.html) page.
+
+Allinea Performance Reports
+---------------------------
+
+Allinea Performance Reports characterize the performance of HPC
+application runs. After executing your application through the tool, a
+synthetic HTML report is generated automatically, containing information
+about several metrics along with clear behavior statements and hints to
+help you improve the efficiency of your runs. Our license is limited to
+64 MPI processes.
+
+ $ module load PerformanceReports/6.0
+ $ perf-report mpirun -n 64 ./my_application argument01 argument02
+
+Read more at the [Allinea Performance
+Reports](debuggers/allinea-performance-reports.html)
+page.
+
+RougeWave Totalview
+-------------------
+
+TotalView is a source- and machine-level debugger for multi-process,
+multi-threaded programs. Its wide range of tools provides ways to
+analyze, organize, and test programs, making it easy to isolate and
+identify problems in individual threads and processes in programs of
+great complexity.
+
+ $ module load TotalView/8.15.4-6-linux-x86-64
+ $ totalview
+
+Read more at the [Totalview](debuggers/total-view.html)
+page.
+
+Vampir trace analyzer
+---------------------
+
+Vampir is a GUI trace analyzer for traces in OTF format.
+
+ $ module load Vampir/8.5.0
+ $ vampir
+
+Read more at the [Vampir](debuggers/vampir.html) page.
+
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diff --git a/converted/docs.it4i.cz/salomon/software/debuggers/aislinn.md b/converted/docs.it4i.cz/salomon/software/debuggers/aislinn.md
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index 0000000000000000000000000000000000000000..ca9d44c11ee2289d3d1dc69e9612a863fa32d191
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/debuggers/aislinn.md
@@ -0,0 +1,150 @@
+Aislinn
+=======
+
+- Aislinn is a dynamic verifier for MPI programs. For a fixed input it
+ covers all possible runs with respect to nondeterminism introduced
+ by MPI. It allows to detect bugs (for sure) that occurs very rare in
+ normal runs.
+- Aislinn detects problems like invalid memory accesses, deadlocks,
+ misuse of MPI, and resource leaks.
+- Aislinn is open-source software; you can use it without any
+ licensing limitations.
+- Web page of the project: <http://verif.cs.vsb.cz/aislinn/>
+
+Note
+
+Aislinn is software developed at IT4Innovations and some parts are still
+considered experimental. If you have any questions or experienced any
+problems, please contact the author: <stanislav.bohm@vsb.cz>.
+
+### Usage
+
+Let us have the following program that contains a bug that is not
+manifested in all runs:
+
+`
+#include <mpi.h>
+#include <stdlib.h>
+
+int main(int argc, char **argv) {
+ int rank;
+
+ MPI_Init(&argc, &argv);
+ MPI_Comm_rank(MPI_COMM_WORLD, &rank);
+
+ if (rank == 0) {
+ int *mem1 = (int*) malloc(sizeof(int) * 2);
+ int *mem2 = (int*) malloc(sizeof(int) * 3);
+ int data;
+ MPI_Recv(&data, 1, MPI_INT, MPI_ANY_SOURCE, 1,
+ MPI_COMM_WORLD, MPI_STATUS_IGNORE);
+ mem1[data] = 10; // <---------- Possible invalid memory write
+ MPI_Recv(&data, 1, MPI_INT, MPI_ANY_SOURCE, 1,
+ MPI_COMM_WORLD, MPI_STATUS_IGNORE);
+ mem2[data] = 10;
+ free(mem1);
+ free(mem2);
+ }
+
+ if (rank == 1 || rank == 2) {
+ MPI_Send(&rank, 1, MPI_INT, 0, 1, MPI_COMM_WORLD);
+ }
+
+ MPI_Finalize();
+ return 0;
+}
+`
+
+The program does the following: process 0 receives two messages from
+anyone and processes 1 and 2 send a message to process 0. If a message
+from process 1 is received first, then the run does not expose the
+error. If a message from process 2 is received first, then invalid
+memory write occurs at line 16.
+
+To verify this program by Aislinn, we first load Aislinn itself:
+
+`
+$ module load aislinn
+`
+
+Now we compile the program by Aislinn implementation of MPI. There are
+`mpicc` for C programs and `mpicxx`{.docutils
+.literal} for C++ programs. Only MPI parts of the verified application
+has to be recompiled; non-MPI parts may remain untouched. Let us assume
+that our program is in `test.cpp`.
+
+`
+$ mpicc -g test.cpp -o test
+`
+
+The `-g` flag is not necessary, but it puts more
+debugging information into the program, hence Aislinn may provide more
+detailed report. The command produces executable file `test`{.docutils
+.literal}.
+
+Now we run the Aislinn itself. The argument `-p 3`
+specifies that we want to verify our program for the case of three MPI
+processes
+
+`
+$ aislinn -p 3 ./test
+==AN== INFO: Aislinn v0.3.0
+==AN== INFO: Found error 'Invalid write'
+==AN== INFO: 1 error(s) found
+==AN== INFO: Report written into 'report.html'
+`
+
+Aislinn found an error and produced HTML report. To view it, we can use
+any browser, e.g.:
+
+ $ firefox report.html
+
+At the beginning of the report there are some basic summaries of the
+verification. In the second part (depicted in the following picture),
+the error is described.
+
+
+It shows us:
+
+ - Error occurs in process 0 in test.cpp on line 16.
+ - Stdout and stderr streams are empty. (The program does not
+ write anything).
+ - The last part shows MPI calls for each process that occurs in the
+ invalid run. The more detailed information about each call can be
+ obtained by mouse cursor.
+
+### Limitations
+
+Since the verification is a non-trivial process there are some of
+limitations.
+
+- The verified process has to terminate in all runs, i.e. we cannot
+ answer the halting problem.
+- The verification is a computationally and memory demanding process.
+ We put an effort to make it efficient and it is an important point
+ for further research. However covering all runs will be always more
+ demanding than techniques that examines only a single run. The good
+ practise is to start with small instances and when it is feasible,
+ make them bigger. The Aislinn is good to find bugs that are hard to
+ find because they occur very rarely (only in a rare scheduling).
+ Such bugs often do not need big instances.
+- Aislinn expects that your program is a "standard MPI" program, i.e.
+ processes communicate only through MPI, the verified program does
+ not interacts with the system in some unusual ways (e.g.
+ opening sockets).
+
+There are also some limitations bounded to the current version and they
+will be removed in the future:
+
+- All files containing MPI calls have to be recompiled by MPI
+ implementation provided by Aislinn. The files that does not contain
+ MPI calls, they do not have to recompiled. Aislinn MPI
+ implementation supports many commonly used calls from MPI-2 and
+ MPI-3 related to point-to-point communication, collective
+ communication, and communicator management. Unfortunately, MPI-IO
+ and one-side communication is not implemented yet.
+- Each MPI can use only one thread (if you use OpenMP, set
+ `OMP_NUM_THREADS` to 1).
+- There are some limitations for using files, but if the program just
+ reads inputs and writes results, it is ok.
+
diff --git a/converted/docs.it4i.cz/salomon/software/debuggers/allinea-ddt.md b/converted/docs.it4i.cz/salomon/software/debuggers/allinea-ddt.md
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+++ b/converted/docs.it4i.cz/salomon/software/debuggers/allinea-ddt.md
@@ -0,0 +1,220 @@
+Allinea Forge (DDT,MAP)
+=======================
+
+
+
+Allinea Forge consist of two tools - debugger DDT and profiler MAP.
+
+Allinea DDT, is a commercial debugger primarily for debugging parallel
+MPI or OpenMP programs. It also has a support for GPU (CUDA) and Intel
+Xeon Phi accelerators. DDT provides all the standard debugging features
+(stack trace, breakpoints, watches, view variables, threads etc.) for
+every thread running as part of your program, or for every process -
+even if these processes are distributed across a cluster using an MPI
+implementation.
+
+Allinea MAP is a profiler for C/C++/Fortran HPC codes. It is designed
+for profiling parallel code, which uses pthreads, OpenMP or MPI.
+
+License and Limitations for the clusters Users
+----------------------------------------------
+
+On the clusters users can debug OpenMP or MPI code that runs up to 64
+parallel processes. In case of debugging GPU or Xeon Phi accelerated
+codes the limit is 8 accelerators. These limitation means that:
+
+- 1 user can debug up 64 processes, or
+- 32 users can debug 2 processes, etc.
+
+In case of debugging on accelerators:
+
+- 1 user can debug on up to 8 accelerators, orÂ
+- 8 users can debug on single accelerator.Â
+
+Compiling Code to run with Forge
+--------------------------------
+
+### Modules
+
+Load all necessary modules to compile the code. For example:Â
+
+ $ module load intel
+ $ module load impi ... or ... module load OpenMPI
+
+Load the Allinea DDT module:
+
+ $ module load Forge
+
+Compile the code:
+
+`
+$ mpicc -g -O0 -o test_debug test.c
+
+$ mpif90 -g -O0 -o test_debug test.f
+`
+
+### Compiler flags
+
+Before debugging, you need to compile your code with theses flags:
+
+-g** : Generates extra debugging information usable by GDB. -g3**
+includes even more debugging information. This option is available for
+GNU and INTEL C/C++ and Fortran compilers.
+
+-O0** : Suppress all optimizations.**
+
+Â
+
+Direct starting a Job with Forge
+--------------------------------
+
+Be sure to log in with an [ X window
+forwarding
+enabled](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html).
+This could mean using the -X in the ssh: Â
+
+ $ ssh -X username@clustername.it4i.cz
+
+Other options is to access login node using VNC. Please see the detailed
+information on [how to
+use graphic user interface on the
+clusters](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html)
+.
+
+From the login node an interactive session **with X windows forwarding**
+(-X option) can be started by following command:Â
+
+ $ qsub -I -X -A NONE-0-0 -q qexp -lselect=1:ncpus=24:mpiprocs=24,walltime=01:00:00Â
+
+Then launch the debugger with the ddt command followed by the name of
+the executable to debug:
+
+ $ ddt test_debug
+
+Forge now has common GUI for both DDT and MAP. In interactive mode, you
+can launch Forge using forge, ddt or map,
+the latter two will just launch forge and swith to the respective
+tab in the common GUI.
+
+A submission window that appears have
+a prefilled path to the executable to debug. You can select the number
+of MPI processors and/or OpenMP threads on which to run and press run.
+Command line arguments to a program can be entered to the
+"Arguments "
+box.
+
+
+Â Â
+
+To start the debugging directly without the submission window, user can
+specify the debugging and execution parameters from the command line.
+For example the number of MPI processes is set by option "-np 4".
+Skipping the dialog is done by "-start" option. To see the list of the
+"ddt" command line parameters, run "ddt --help". Â
+
+ ddt -start -np 4 ./hello_debug_impi
+
+All of the above text also applies for MAP, just replace ddt command
+with map.
+
+Reverse connect
+---------------
+
+Forge now provides a new convenient mode of operation, called Reverse
+connect. Instead of launching a job from the GUI, the process is
+reserved - DDT/MAP is launched as a server in the job which then
+connects to a running instance of your GUI.
+
+To use Reverse connect, use a jobscript that you would normally use to
+launch your application, just prepend ddt/map --connect to your
+application:
+
+ map --connect mpirun -np 24 ./mpi-test
+ ddt --connect mpirun -np 24 ./mpi-test
+
+Launch Forge GUI on login node and submit the job using qsub. When the
+job starts running, Forge will ask you to accept the connection:
+
+
+
+After accepting the request, you can start remote profiling/debugging.
+
+Xeon Phi
+--------
+
+Forge allows debugging and profiling of both offload and native mode
+Xeon Phi programs.
+
+### Offload mode
+
+It is recommended to set the following environment values on the offload
+host:
+
+ export MYO_WATCHDOG_MONITOR=-1 # To make sure the host process isn't killed when we enter a debugging session
+ export AMPLXE_COI_DEBUG_SUPPORT=true # To make sure that debugging symbols are accessible on the host and the card
+ unset OFFLOAD_MAIN # To make sure allinea DDT can attach to offloaded codes
+
+Then use one of the above mentioned methods to launch Forge. (Reverse
+connect also works.)
+
+### Native mode
+
+Native mode programs can be profiled/debugged using the remote launch
+feature. First, you need to create a script that will setup the
+environment on the Phi card. An example:
+
+ #!/bin/bash
+ # adjust PATH and LD_LIBRARY_PATH according to the toolchain/libraries your app is using.
+ export PATH=/apps/all/impi/5.0.3.048-iccifort-2015.3.187/mic/bin:$PATH
+ export LD_LIBRARY_PATH=/apps/all/impi/5.0.3.048-iccifort-2015.3.187/mic/lib:/apps/all/ifort/2015.3.187/lib/mic:/apps/all/icc/2015.3.187/lib/mic:$LD_LIBRARY_PATH
+ export MIC_OMP_NUM_THREADS=60
+ export MYO_WATCHDOG_MONITOR=-1
+ export AMPLXE_COI_DEBUG_SUPPORT=true
+ unset OFFLOAD_MAIN
+ export I_MPI_MIC=1
+
+Save the script in eg. ~/remote-mic.sh.
+Now, start an interactive graphical session on a node with
+accelerator:
+
+ $ qsub â€IX â€q qexp â€l select=1:ncpus=24:accelerator=True
+
+Launch Forge :
+
+ $ module load Forge
+ $ forge&
+
+Now click on the remote launch drop-down list, select "Configure..." and
+Add a new remote connection with the following parameters:
+
+Connection name: mic0
+
+Hostname: mic0
+
+Remote Installation Directory:Â /apps/all/Forge/5.1-43967/
+
+Remote script: ~/remote-mic.sh
+
+You can click Test Remote Launch to verify the configuration. After you
+save the remote launch configuration and select it in the dropdown list,
+you can use the Run button in the main windows to remotely launch your
+program on mic0.
+
+Documentation
+-------------
+
+Users can find original User Guide after loading the Forge module:Â
+
+ $EBROOTFORGE/doc/userguide-forge.pdf
+
+Â
+
+Â
+
+Â [1] Discipline, Magic, Inspiration and Science: Best Practice
+Debugging with Allinea DDT, Workshop conducted at LLNL by Allinea on May
+10, 2013,
+[link](https://computing.llnl.gov/tutorials/allineaDDT/index.html)
+
+Â
+
diff --git a/converted/docs.it4i.cz/salomon/software/debuggers/allinea-performance-reports.md b/converted/docs.it4i.cz/salomon/software/debuggers/allinea-performance-reports.md
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@@ -0,0 +1,76 @@
+Allinea Performance Reports
+===========================
+
+quick application profiling
+
+
+
+Introduction
+------------
+
+Allinea Performance Reports characterize the performance of HPC
+application runs. After executing your application through the tool, a
+synthetic HTML report is generated automatically, containing information
+about several metrics along with clear behavior statements and hints to
+help you improve the efficiency of your runs.
+
+The Allinea Performance Reports is most useful in profiling MPI
+programs.
+
+Our license is limited to 64 MPI processes.
+
+Modules
+-------
+
+Allinea Performance Reports version 6.0 is available
+
+ $ module load PerformanceReports/6.0
+
+The module sets up environment variables, required for using the Allinea
+Performance Reports.Â
+
+Usage
+-----
+
+Use the the perf-report wrapper on your (MPI) program.
+
+Instead of [running your MPI program the usual
+way](../mpi-1.html), use the the perf report wrapper:
+
+ $ perf-report mpirun ./mympiprog.x
+
+The mpi program will run as usual. The perf-report creates two
+additional files, in *.txt and *.html format, containing the
+performance report. Note that demanding MPI
+codes should be run within [ the queue
+system](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+
+Example
+-------
+
+In this example, we will be profiling the mympiprog.x MPI program, using
+Allinea performance reports. Assume that the code is compiled with intel
+compilers and linked against intel MPI library:
+
+First, we allocate some nodes via the express queue:
+
+ $ qsub -q qexp -l select=2:ppn=24:mpiprocs=24:ompthreads=1 -I
+ qsub: waiting for job 262197.dm2 to start
+ qsub: job 262197.dm2 ready
+
+Then we load the modules and run the program the usual way:
+
+ $ module load intel impi PerfReports/6.0
+ $ mpirun ./mympiprog.x
+
+Now lets profile the code:
+
+ $ perf-report mpirun ./mympiprog.x
+
+Performance report files
+[mympiprog_32p*.txt](mympiprog_32p_2014-10-15_16-56.txt)
+and
+[mympiprog_32p*.html](mympiprog_32p_2014-10-15_16-56.html)
+were created. We can see that the code is very efficient on MPI and is
+CPU bounded.
+
diff --git a/converted/docs.it4i.cz/salomon/software/debuggers/ddt1.png b/converted/docs.it4i.cz/salomon/software/debuggers/ddt1.png
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@@ -0,0 +1,137 @@
+Intel VTune Amplifier XE
+========================
+
+
+
+Introduction
+------------
+
+Intel*® *VTune™ >Amplifier, part of Intel Parallel studio, is a GUI
+profiling tool designed for Intel processors. It offers a graphical
+performance analysis of single core and multithreaded applications. A
+highlight of the features:
+
+- Hotspot analysis
+- Locks and waits analysis
+- Low level specific counters, such as branch analysis and memory
+ bandwidth
+- Power usage analysis - frequency and sleep states.
+
+
+
+Usage
+-----
+
+To profile an application with VTune Amplifier, special kernel
+modules need to be loaded. The modules are not loaded on the login
+nodes, thus direct profiling on login nodes is not possible. By default,
+the kernel modules ale not loaded on compute nodes neither. In order to
+have the modules loaded, you need to specify vtune=version PBS resource
+at job submit. The version is the same as for *environment module*. For
+example to use
+VTune/2016_update1:
+
+ $ qsub -q qexp -A OPEN-0-0 -I -l select=1,vtune=2016_update1
+
+After that, you can verify the modules sep*, pax and vtsspp are present
+in the kernel :
+
+ $ lsmod | grep -e sep -e pax -e vtsspp
+ vtsspp 362000 0
+ sep3_15 546657 0
+ pax 4312 0
+
+To launch the GUI, first load the module:
+
+ $ module add VTune/2016_update1
+
+ class="s1">and launch the GUI :
+
+ $Â amplxe-gui
+
+The GUI will open in new window. Click on "*New Project...*" to
+create a new project. After clicking *OK*, a new window with project
+properties will appear. Â At "*Application:*", select the bath to your
+binary you want to profile (the binary should be compiled with -g flag).
+Some additional options such as command line arguments can be selected.
+At "*Managed code profiling mode:*" select "*Native*" (unless you want
+to profile managed mode .NET/Mono applications). After clicking *OK*,
+your project is created.
+
+To run a new analysis, click "*New analysis...*". You will see a list of
+possible analysis. Some of them will not be possible on the current CPU
+(eg. Intel Atom analysis is not possible on Sandy bridge CPU), the GUI
+will show an error box if you select the wrong analysis. For example,
+select "*Advanced Hotspots*". Clicking on *Start *will start profiling
+of the application.
+
+Remote Analysis
+---------------
+
+VTune Amplifier also allows a form of remote analysis. In this mode,
+data for analysis is collected from the command line without GUI, and
+the results are then loaded to GUI on another machine. This allows
+profiling without interactive graphical jobs. To perform a remote
+analysis, launch a GUI somewhere, open the new analysis window and then
+click the button "*Command line*" in bottom right corner. It will show
+the command line needed to perform the selected analysis.
+
+The command line will look like this:
+
+ /apps/all/VTune/2016_update1/vtune_amplifier_xe_2016.1.1.434111/bin64/amplxe-cl -collect advanced-hotspots -app-working-dir /home/sta545/tmp -- /home/sta545/tmp/sgemm
+
+Copy the line to clipboard and then you can paste it in your jobscript
+or in command line. After the collection is run, open the GUI once
+again, click the menu button in the upper right corner, and select
+"*Open > Result...*". The GUI will load the results from the run.
+
+Xeon Phi
+--------
+
+It is possible to analyze both native and offloaded Xeon Phi
+applications.Â
+
+### Native mode
+
+This mode is useful for native Xeon Phi applications launched directly
+on the card. In *Analysis Target* window, select *Intel Xeon Phi
+coprocessor (native), *choose path to the binary and MIC card to run on.
+
+### Offload mode
+
+This mode is useful for applications that are launched from the host and
+use offload, OpenCL or mpirun. In *Analysis Target* window,
+select *Intel Xeon Phi coprocessor (native), *choose path to the binary
+and MIC card to run on.
+
+Â
+
+If the analysis is interrupted or aborted, further analysis on the card
+might be impossible and you will get errors like "ERROR connecting to
+MIC card". In this case please contact our support to reboot the MIC
+card.
+
+You may also use remote analysis to collect data from the MIC and then
+analyze it in the GUI later :
+
+Native launch:
+
+ $ /apps/all/VTune/2016_update1/vtune_amplifier_xe_2016.1.1.434111/bin64/amplxe-cl -target-system mic-native:0 -collect advanced-hotspots -- /home/sta545/tmp/vect-add-mic
+
+Host launch:
+
+ $ /apps/all/VTune/2016_update1/vtune_amplifier_xe_2016.1.1.434111/bin64/amplxe-cl -target-system mic-host-launch:0 -collect advanced-hotspots -- /home/sta545/tmp/sgemm
+
+You can obtain this command line by pressing the "Command line..."
+button on Analysis Type screen.Â
+
+References
+----------
+
+1. ><https://www.rcac.purdue.edu/tutorials/phi/PerformanceTuningXeonPhi-Tullos.pdf>Â Performance
+ Tuning for Intel® Xeon Phi™ Coprocessors
+2. ><https://software.intel.com/en-us/intel-vtune-amplifier-xe-support/documentation> >Intel®
+ VTune™ Amplifier Support
+3. ><https://software.intel.com/en-us/amplifier_help_linux>Â Linux
+ user guide
+
diff --git a/converted/docs.it4i.cz/salomon/software/debuggers/report.png b/converted/docs.it4i.cz/salomon/software/debuggers/report.png
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@@ -0,0 +1,87 @@
+Debuggers and profilers summary
+===============================
+
+
+
+Introduction
+------------
+
+We provide state of the art programms and tools to develop, profile and
+debug HPC codes at IT4Innovations.
+On these pages, we provide an overview of the profiling and debugging
+tools available on Anslem at IT4I.
+
+Intel debugger
+--------------
+
+Intel debugger is no longer available since Parallel Studio version 2015
+
+The intel debugger version 13.0 is available, via module intel. The
+debugger works for applications compiled with C and C++ compiler and the
+ifort fortran 77/90/95 compiler. The debugger provides java GUI
+environment. Use [X
+display](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html)
+for running the GUI.
+
+ $ module load intel
+ $ idb
+
+Read more at the [Intel
+Debugger](../intel-suite/intel-debugger.html) page.
+
+Allinea Forge (DDT/MAP)
+-----------------------
+
+Allinea DDT, is a commercial debugger primarily for debugging parallel
+MPI or OpenMP programs. It also has a support for GPU (CUDA) and Intel
+Xeon Phi accelerators. DDT provides all the standard debugging features
+(stack trace, breakpoints, watches, view variables, threads etc.) for
+every thread running as part of your program, or for every process -
+even if these processes are distributed across a cluster using an MPI
+implementation.
+
+ $ module load Forge
+ $ forge
+
+Read more at the [Allinea DDT](allinea-ddt.html) page.
+
+Allinea Performance Reports
+---------------------------
+
+Allinea Performance Reports characterize the performance of HPC
+application runs. After executing your application through the tool, a
+synthetic HTML report is generated automatically, containing information
+about several metrics along with clear behavior statements and hints to
+help you improve the efficiency of your runs. Our license is limited to
+64 MPI processes.
+
+ $ module load PerformanceReports/6.0
+ $ perf-report mpirun -n 64 ./my_application argument01 argument02
+
+Read more at the [Allinea Performance
+Reports](allinea-performance-reports.html) page.
+
+RougeWave Totalview
+-------------------
+
+TotalView is a source- and machine-level debugger for multi-process,
+multi-threaded programs. Its wide range of tools provides ways to
+analyze, organize, and test programs, making it easy to isolate and
+identify problems in individual threads and processes in programs of
+great complexity.
+
+ $ module load TotalView/8.15.4-6-linux-x86-64
+ $ totalview
+
+Read more at the [Totalview](total-view.html) page.
+
+Vampir trace analyzer
+---------------------
+
+Vampir is a GUI trace analyzer for traces in OTF format.
+
+ $ module load Vampir/8.5.0
+ $ vampir
+
+Read more at the [Vampir](vampir.html) page.
+
diff --git a/converted/docs.it4i.cz/salomon/software/debuggers/total-view.md b/converted/docs.it4i.cz/salomon/software/debuggers/total-view.md
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@@ -0,0 +1,157 @@
+Total View
+==========
+
+TotalView is a GUI-based source code multi-process, multi-thread
+debugger.
+
+License and Limitations for cluster Users
+-----------------------------------------
+
+On the cluster users can debug OpenMP or MPI code that runs up to 64
+parallel processes. These limitation means that:
+
+Â Â Â 1 user can debug up 64 processes, or
+Â Â Â 32 users can debug 2 processes, etc.
+
+Debugging of GPU accelerated codes is also supported.
+
+You can check the status of the licenses
+[here](https://extranet.it4i.cz/rsweb/anselm/license/totalview).
+
+Compiling Code to run with TotalView
+------------------------------------
+
+### Modules
+
+Load all necessary modules to compile the code. For example:
+
+ module load intel
+
+ module load impi  ... or ... module load OpenMPI/X.X.X-icc
+
+Load the TotalView module:
+
+ module load TotalView/8.15.4-6-linux-x86-64
+
+Compile the code:
+
+ mpicc -g -O0 -o test_debug test.c
+
+ mpif90 -g -O0 -o test_debug test.f
+
+### Compiler flags
+
+Before debugging, you need to compile your code with theses flags:
+
+-g** : Generates extra debugging information usable by GDB. -g3**
+includes even more debugging information. This option is available for
+GNU and INTEL C/C++ and Fortran compilers.
+
+-O0** : Suppress all optimizations.**
+
+Starting a Job with TotalView
+-----------------------------
+
+Be sure to log in with an X window forwarding enabled. This could mean
+using the -X in the ssh:Â
+
+ ssh -X username@salomon.it4i.cz
+
+Other options is to access login node using VNC. Please see the detailed
+information on how to use graphic user interface on Anselm
+[here](https://docs.it4i.cz/salomon/software/debuggers/resolveuid/11e53ad0d2fd4c5187537f4baeedff33#VNC).
+
+From the login node an interactive session with X windows forwarding (-X
+option) can be started by following command:
+
+ qsub -I -X -A NONE-0-0 -q qexp -lselect=1:ncpus=24:mpiprocs=24,walltime=01:00:00
+
+Then launch the debugger with the totalview command followed by the name
+of the executable to debug.
+
+### Debugging a serial code
+
+To debug a serial code use:
+
+ totalview test_debug
+
+### Debugging a parallel code - option 1
+
+To debug a parallel code compiled with >**OpenMPI** you need
+to setup your TotalView environment:Â
+
+Please note:** To be able to run parallel debugging procedure from the
+command line without stopping the debugger in the mpiexec source code
+you have to add the following function to your **~/.tvdrc** file:
+
+ proc mpi_auto_run_starter {loaded_id} {
+ Â Â Â set starter_programs {mpirun mpiexec orterun}
+ Â Â Â set executable_name [TV::symbol get $loaded_id full_pathname]
+ Â Â Â set file_component [file tail $executable_name]
+
+ Â Â Â if {[lsearch -exact $starter_programs $file_component] != -1} {
+ Â Â Â Â Â Â Â puts "*************************************"
+ Â Â Â Â Â Â Â puts "Automatically starting $file_component"
+ Â Â Â Â Â Â Â puts "*************************************"
+ Â Â Â Â Â Â Â dgo
+ Â Â Â }
+ }
+
+ # Append this function to TotalView's image load callbacks so that
+ # TotalView run this program automatically.
+
+ dlappend TV::image_load_callbacks mpi_auto_run_starter
+
+The source code of this function can be also found in
+
+ /apps/all/OpenMPI/1.10.1-GNU-4.9.3-2.25/etc/openmpi-totalview.tcl
+
+You can also add only following line to you ~/.tvdrc file instead of
+the entire function:
+
+source /apps/all/OpenMPI/1.10.1-GNU-4.9.3-2.25/etc/openmpi-totalview.tcl**
+
+You need to do this step only once. See also [OpenMPI FAQ
+entry](https://www.open-mpi.org/faq/?category=running#run-with-tv)
+
+Now you can run the parallel debugger using:
+
+ mpirun -tv -n 5 ./test_debug
+
+When following dialog appears click on "Yes"
+
+
+
+At this point the main TotalView GUI window will appear and you can
+insert the breakpoints and start debugging:
+
+
+
+### Debugging a parallel code - option 2
+
+Other option to start new parallel debugging session from a command line
+is to let TotalView to execute mpirun by itself. In this case user has
+to specify a MPI implementation used to compile the source code.Â
+
+The following example shows how to start debugging session with Intel
+MPI:
+
+ module load intel/2015b-intel-2015b impi/5.0.3.048-iccifort-2015.3.187-GNU-5.1.0-2.25 TotalView/8.15.4-6-linux-x86-64
+
+ totalview -mpi "Intel MPI-Hydra" -np 8 ./hello_debug_impi
+
+After running previous command you will see the same window as shown in
+the screenshot above.
+
+More information regarding the command line parameters of the TotalView
+can be found TotalView Reference Guide, Chapter 7: TotalView Command
+Syntax. Â
+
+Documentation
+-------------
+
+[1] The [TotalView
+documentation](http://www.roguewave.com/support/product-documentation/totalview-family.aspx#totalview)
+web page is a good resource for learning more about some of the advanced
+TotalView features.
+
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+Valgrind
+========
+
+Valgrind is a tool for memory debugging and profiling.
+
+About Valgrind
+--------------
+
+Valgrind is an open-source tool, used mainly for debuggig memory-related
+problems, such as memory leaks, use of uninitalized memory etc. in C/C++
+applications. The toolchain was however extended over time with more
+functionality, such as debugging of threaded applications, cache
+profiling, not limited only to C/C++.
+
+Valgind is an extremely useful tool for debugging memory errors such as
+[off-by-one](http://en.wikipedia.org/wiki/Off-by-one_error).
+Valgrind uses a virtual machine and dynamic recompilation of binary
+code, because of that, you can expect that programs being debugged by
+Valgrind run 5-100 times slower.
+
+The main tools available in Valgrind are :
+
+- **Memcheck**, the original, must used and default tool. Verifies
+ memory access in you program and can detect use of unitialized
+ memory, out of bounds memory access, memory leaks, double free, etc.
+- **Massif**, a heap profiler.
+- **Hellgrind** and **DRD** can detect race conditions in
+ multi-threaded applications.
+- **Cachegrind**, a cache profiler.
+- **Callgrind**, a callgraph analyzer.
+- For a full list and detailed documentation, please refer to the
+ [official Valgrind
+ documentation](http://valgrind.org/docs/).
+
+Installed versions
+------------------
+
+There are two versions of Valgrind available on the cluster.
+
+- >Version 3.8.1, installed by operating system vendor
+ in /usr/bin/valgrind.
+ >This version is available by default, without the need
+ to load any module. This version however does not provide additional
+ MPI support. Also, it does not support AVX2 instructions,
+ **debugging of an AVX2-enabled executable with this version will
+ fail**
+- >Version 3.11.0 built by ICC with support for Intel MPI,
+ available in
+ [module](../../environment-and-modules.html)Â
+ Valgrind/3.11.0-intel-2015b. After loading
+ the module, this version replaces the default valgrind.
+- Version 3.11.0 built by GCC with support for Open MPI, module
+ Valgrind/3.11.0-foss-2015b
+
+Usage
+-----
+
+Compile the application which you want to debug as usual. It is
+advisable to add compilation flags -g (to
+add debugging information to the binary so that you will see original
+source code lines in the output) and -O0
+(to disable compiler optimizations).Â
+
+For example, lets look at this C code, which has two problems :
+
+ #include <stdlib.h>
+
+ void f(void)
+ {
+ int* x = malloc(10 * sizeof(int));
+ x[10] = 0; // problem 1: heap block overrun
+ } // problem 2: memory leak -- x not freed
+
+ int main(void)
+ {
+ f();
+ return 0;
+ }
+
+Now, compile it with Intel compiler :
+
+ $ module add intel
+ $ icc -g valgrind-example.c -o valgrind-exampleÂ
+
+Now, lets run it with Valgrind. The syntax is :
+
+ valgrind [valgrind options] <your program
+binary> [your program options]
+
+If no Valgrind options are specified, Valgrind defaults to running
+Memcheck tool. Please refer to the Valgrind documentation for a full
+description of command line options.
+
+ $ valgrind ./valgrind-example
+ ==12652== Memcheck, a memory error detector
+ ==12652== Copyright (C) 2002-2013, and GNU GPL'd, by Julian Seward et al.
+ ==12652== Using Valgrind-3.9.0 and LibVEX; rerun with -h for copyright info
+ ==12652== Command: ./valgrind-example
+ ==12652==
+ ==12652== Invalid write of size 4
+ ==12652== at 0x40053E: f (valgrind-example.c:6)
+ ==12652== by 0x40054E: main (valgrind-example.c:11)
+ ==12652== Address 0x5861068 is 0 bytes after a block of size 40 alloc'd
+ ==12652== at 0x4C27AAA: malloc (vg_replace_malloc.c:291)
+ ==12652== by 0x400528: f (valgrind-example.c:5)
+ ==12652== by 0x40054E: main (valgrind-example.c:11)
+ ==12652==
+ ==12652==
+ ==12652== HEAP SUMMARY:
+ ==12652== in use at exit: 40 bytes in 1 blocks
+ ==12652== total heap usage: 1 allocs, 0 frees, 40 bytes allocated
+ ==12652==
+ ==12652== LEAK SUMMARY:
+ ==12652== definitely lost: 40 bytes in 1 blocks
+ ==12652== indirectly lost: 0 bytes in 0 blocks
+ ==12652== possibly lost: 0 bytes in 0 blocks
+ ==12652== still reachable: 0 bytes in 0 blocks
+ ==12652== suppressed: 0 bytes in 0 blocks
+ ==12652== Rerun with --leak-check=full to see details of leaked memory
+ ==12652==
+ ==12652== For counts of detected and suppressed errors, rerun with: -v
+ ==12652== ERROR SUMMARY: 1 errors from 1 contexts (suppressed: 6 from 6)
+
+In the output we can see that Valgrind has detected both errors - the
+off-by-one memory access at line 5 and a memory leak of 40 bytes. If we
+want a detailed analysis of the memory leak, we need to run Valgrind
+with --leak-check=full option :
+
+ $ valgrind --leak-check=full ./valgrind-example
+ ==23856== Memcheck, a memory error detector
+ ==23856== Copyright (C) 2002-2010, and GNU GPL'd, by Julian Seward et al.
+ ==23856== Using Valgrind-3.6.0 and LibVEX; rerun with -h for copyright info
+ ==23856== Command: ./valgrind-example
+ ==23856==
+ ==23856== Invalid write of size 4
+ ==23856== at 0x40067E: f (valgrind-example.c:6)
+ ==23856== by 0x40068E: main (valgrind-example.c:11)
+ ==23856== Address 0x66e7068 is 0 bytes after a block of size 40 alloc'd
+ ==23856== at 0x4C26FDE: malloc (vg_replace_malloc.c:236)
+ ==23856== by 0x400668: f (valgrind-example.c:5)
+ ==23856== by 0x40068E: main (valgrind-example.c:11)
+ ==23856==
+ ==23856==
+ ==23856== HEAP SUMMARY:
+ ==23856== in use at exit: 40 bytes in 1 blocks
+ ==23856== total heap usage: 1 allocs, 0 frees, 40 bytes allocated
+ ==23856==
+ ==23856== 40 bytes in 1 blocks are definitely lost in loss record 1 of 1
+ ==23856== at 0x4C26FDE: malloc (vg_replace_malloc.c:236)
+ ==23856== by 0x400668: f (valgrind-example.c:5)
+ ==23856== by 0x40068E: main (valgrind-example.c:11)
+ ==23856==
+ ==23856== LEAK SUMMARY:
+ ==23856== definitely lost: 40 bytes in 1 blocks
+ ==23856== indirectly lost: 0 bytes in 0 blocks
+ ==23856== possibly lost: 0 bytes in 0 blocks
+ ==23856== still reachable: 0 bytes in 0 blocks
+ ==23856== suppressed: 0 bytes in 0 blocks
+ ==23856==
+ ==23856== For counts of detected and suppressed errors, rerun with: -v
+ ==23856== ERROR SUMMARY: 2 errors from 2 contexts (suppressed: 6 from 6)
+
+Now we can see that the memory leak is due to the
+malloc() at line 6.
+
+Usage with MPI
+---------------------------
+
+Although Valgrind is not primarily a parallel debugger, it can be used
+to debug parallel applications as well. When launching your parallel
+applications, prepend the valgrind command. For example :
+
+ $ mpirun -np 4 valgrind myapplication
+
+The default version without MPI support will however report a large
+number of false errors in the MPI library, such as :
+
+ ==30166== Conditional jump or move depends on uninitialised value(s)
+ ==30166== at 0x4C287E8: strlen (mc_replace_strmem.c:282)
+ ==30166== by 0x55443BD: I_MPI_Processor_model_number (init_interface.c:427)
+ ==30166== by 0x55439E0: I_MPI_Processor_arch_code (init_interface.c:171)
+ ==30166== by 0x558D5AE: MPID_nem_impi_init_shm_configuration (mpid_nem_impi_extensions.c:1091)
+ ==30166== by 0x5598F4C: MPID_nem_init_ckpt (mpid_nem_init.c:566)
+ ==30166== by 0x5598B65: MPID_nem_init (mpid_nem_init.c:489)
+ ==30166== by 0x539BD75: MPIDI_CH3_Init (ch3_init.c:64)
+ ==30166== by 0x5578743: MPID_Init (mpid_init.c:193)
+ ==30166== by 0x554650A: MPIR_Init_thread (initthread.c:539)
+ ==30166== by 0x553369F: PMPI_Init (init.c:195)
+ ==30166== by 0x4008BD: main (valgrind-example-mpi.c:18)
+
+so it is better to use the MPI-enabled valgrind from module. The MPI
+versions requires library :Â
+
+$EBROOTVALGRIND/lib/valgrind/libmpiwrap-amd64-linux.so
+
+which must be included in the LD_PRELOAD
+environment variable.
+
+Lets look at this MPI example :
+
+ #include <stdlib.h>
+ #include <mpi.h>Â
+
+ int main(int argc, char *argv[])
+ {
+ Â Â Â Â Â int *data = malloc(sizeof(int)*99);
+
+ Â Â Â Â Â MPI_Init(&argc, &argv);
+ Â Â Â Â MPI_Bcast(data, 100, MPI_INT, 0, MPI_COMM_WORLD);
+ Â Â Â Â Â MPI_Finalize();Â
+
+ Â Â Â Â Â Â Â return 0;
+ }
+
+There are two errors - use of uninitialized memory and invalid length of
+the buffer. Lets debug it with valgrind :
+
+ $ module add intel impi
+ $ mpiicc -g valgrind-example-mpi.c -o valgrind-example-mpi
+ $ module add Valgrind/3.11.0-intel-2015b
+ $ mpirun -np 2 -env LD_PRELOAD $EBROOTVALGRIND/lib/valgrind/libmpiwrap-amd64-linux.so valgrind ./valgrind-example-mpi
+
+Prints this output : (note that there is output printed for every
+launched MPI process)
+
+ ==31318== Memcheck, a memory error detector
+ ==31318== Copyright (C) 2002-2013, and GNU GPL'd, by Julian Seward et al.
+ ==31318== Using Valgrind-3.9.0 and LibVEX; rerun with -h for copyright info
+ ==31318== Command: ./valgrind-example-mpi
+ ==31318==
+ ==31319== Memcheck, a memory error detector
+ ==31319== Copyright (C) 2002-2013, and GNU GPL'd, by Julian Seward et al.
+ ==31319== Using Valgrind-3.9.0 and LibVEX; rerun with -h for copyright info
+ ==31319== Command: ./valgrind-example-mpi
+ ==31319==
+ valgrind MPI wrappers 31319: Active for pid 31319
+ valgrind MPI wrappers 31319: Try MPIWRAP_DEBUG=help for possible options
+ valgrind MPI wrappers 31318: Active for pid 31318
+ valgrind MPI wrappers 31318: Try MPIWRAP_DEBUG=help for possible options
+ ==31319== Unaddressable byte(s) found during client check request
+ ==31319== at 0x4E35974: check_mem_is_addressable_untyped (libmpiwrap.c:960)
+ ==31319== by 0x4E5D0FE: PMPI_Bcast (libmpiwrap.c:908)
+ ==31319== by 0x400911: main (valgrind-example-mpi.c:20)
+ ==31319== Address 0x69291cc is 0 bytes after a block of size 396 alloc'd
+ ==31319== at 0x4C27AAA: malloc (vg_replace_malloc.c:291)
+ ==31319== by 0x4007BC: main (valgrind-example-mpi.c:8)
+ ==31319==
+ ==31318== Uninitialised byte(s) found during client check request
+ ==31318== at 0x4E3591D: check_mem_is_defined_untyped (libmpiwrap.c:952)
+ ==31318== by 0x4E5D06D: PMPI_Bcast (libmpiwrap.c:908)
+ ==31318== by 0x400911: main (valgrind-example-mpi.c:20)
+ ==31318== Address 0x6929040 is 0 bytes inside a block of size 396 alloc'd
+ ==31318== at 0x4C27AAA: malloc (vg_replace_malloc.c:291)
+ ==31318== by 0x4007BC: main (valgrind-example-mpi.c:8)
+ ==31318==
+ ==31318== Unaddressable byte(s) found during client check request
+ ==31318== at 0x4E3591D: check_mem_is_defined_untyped (libmpiwrap.c:952)
+ ==31318== by 0x4E5D06D: PMPI_Bcast (libmpiwrap.c:908)
+ ==31318== by 0x400911: main (valgrind-example-mpi.c:20)
+ ==31318== Address 0x69291cc is 0 bytes after a block of size 396 alloc'd
+ ==31318== at 0x4C27AAA: malloc (vg_replace_malloc.c:291)
+ ==31318== by 0x4007BC: main (valgrind-example-mpi.c:8)
+ ==31318==
+ ==31318==
+ ==31318== HEAP SUMMARY:
+ ==31318== in use at exit: 3,172 bytes in 67 blocks
+ ==31318== total heap usage: 191 allocs, 124 frees, 81,203 bytes allocated
+ ==31318==
+ ==31319==
+ ==31319== HEAP SUMMARY:
+ ==31319== in use at exit: 3,172 bytes in 67 blocks
+ ==31319== total heap usage: 175 allocs, 108 frees, 48,435 bytes allocated
+ ==31319==
+ ==31318== LEAK SUMMARY:
+ ==31318== definitely lost: 408 bytes in 3 blocks
+ ==31318== indirectly lost: 256 bytes in 1 blocks
+ ==31318== possibly lost: 0 bytes in 0 blocks
+ ==31318== still reachable: 2,508 bytes in 63 blocks
+ ==31318== suppressed: 0 bytes in 0 blocks
+ ==31318== Rerun with --leak-check=full to see details of leaked memory
+ ==31318==
+ ==31318== For counts of detected and suppressed errors, rerun with: -v
+ ==31318== Use --track-origins=yes to see where uninitialised values come from
+ ==31318== ERROR SUMMARY: 2 errors from 2 contexts (suppressed: 4 from 4)
+ ==31319== LEAK SUMMARY:
+ ==31319== definitely lost: 408 bytes in 3 blocks
+ ==31319== indirectly lost: 256 bytes in 1 blocks
+ ==31319== possibly lost: 0 bytes in 0 blocks
+ ==31319== still reachable: 2,508 bytes in 63 blocks
+ ==31319== suppressed: 0 bytes in 0 blocks
+ ==31319== Rerun with --leak-check=full to see details of leaked memory
+ ==31319==
+ ==31319== For counts of detected and suppressed errors, rerun with: -v
+ ==31319== ERROR SUMMARY: 1 errors from 1 contexts (suppressed: 4 from 4)
+
+We can see that Valgrind has reported use of unitialised memory on the
+master process (which reads the array to be broadcasted) and use of
+unaddresable memory on both processes.
+
diff --git a/converted/docs.it4i.cz/salomon/software/debuggers/vampir.md b/converted/docs.it4i.cz/salomon/software/debuggers/vampir.md
new file mode 100644
index 0000000000000000000000000000000000000000..9d213a4212613538afaf684b13c9a01e59f6eaad
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/debuggers/vampir.md
@@ -0,0 +1,32 @@
+Vampir
+======
+
+Vampir is a commercial trace analysis and visualisation tool. It can
+work with traces in OTF and OTF2 formats. It does not have the
+functionality to collect traces, you need to use a trace collection tool
+(such as [Score-P](score-p.html)) first to collect the
+traces.
+
+
+-
+
+Installed versions
+------------------
+
+Version 8.5.0 is currently installed as module
+Vampir/8.5.0 :
+
+ $ module load Vampir/8.5.0
+ $ vampir &
+
+User manual
+-----------
+
+You can find the detailed user manual in PDF format in
+$EBROOTVAMPIR/doc/vampir-manual.pdf
+
+References
+----------
+
+1. <https://www.vampir.eu>
+
diff --git a/converted/docs.it4i.cz/salomon/software/debuggers/vtune-amplifier.png b/converted/docs.it4i.cz/salomon/software/debuggers/vtune-amplifier.png
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diff --git a/converted/docs.it4i.cz/salomon/software/intel-suite/intel-advisor.md b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-advisor.md
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index 0000000000000000000000000000000000000000..805e7d905e3995fbc824d02091d6cefc569f374d
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-advisor.md
@@ -0,0 +1,54 @@
+Intel Advisor
+=============
+
+is tool aiming to assist you in vectorization and threading of your
+code. You can use it to profile your application and identify
+loops, that could benefit from vectorization and/or threading
+parallelism.
+
+Installed versions
+------------------
+
+The following versions are currently available on Salomon as modules:
+
+ --------- |---|---|-------------
+ |---|---|
+ |2016 Update 2|Advisor/2016_update2|
+ --------- |---|---|-------------
+
+Usage
+-----
+
+Your program should be compiled with -g switch to include symbol names.
+You should compile with -O2 or higher to see code that is already
+vectorized by the compiler.
+
+Profiling is possible either directly from the GUI, or from command
+line.
+
+To profile from GUI, launch Advisor:
+
+ $ advixe-gui
+
+Then select menu File -> New -> Project. Choose a directory to
+save project data to. After clicking OK, Project properties window will
+appear, where you can configure path to your binary, launch arguments,
+working directory etc. After clicking OK, the project is ready.
+
+In the left pane, you can switch between Vectorization and Threading
+workflows. Each has several possible steps which you can execute by
+clicking Collect button. Alternatively, you can click on Command Line,
+to see the command line required to run the analysis directly from
+command line.
+
+References
+----------
+
+1. [Intel® Advisor 2015 Tutorial: Find Where to Add Parallelism - C++
+ Sample](https://software.intel.com/en-us/advisorxe_2015_tut_lin_c)
+2. [Product
+ page](https://software.intel.com/en-us/intel-advisor-xe)
+3. [Documentation](https://software.intel.com/en-us/intel-advisor-2016-user-guide-linux)
+
+Â
+
diff --git a/converted/docs.it4i.cz/salomon/software/intel-suite/intel-compilers.md b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-compilers.md
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index 0000000000000000000000000000000000000000..b846db42aa19e40378c81fa7a07bef2bde776b87
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-compilers.md
@@ -0,0 +1,71 @@
+Intel Compilers
+===============
+
+
+
+The Intel compilers in multiple versions are available, via module
+intel. The compilers include the icc C and C++ compiler and the ifort
+fortran 77/90/95 compiler.
+
+ $ module load intel
+ $ icc -v
+ $ ifort -v
+
+The intel compilers provide for vectorization of the code, via the AVX2
+instructions and support threading parallelization via OpenMP
+
+For maximum performance on the Salomon cluster compute nodes, compile
+your programs using the AVX2 instructions, with reporting where the
+vectorization was used. We recommend following compilation options for
+high performance
+
+ $ icc -ipo -O3 -xCORE-AVX2 -qopt-report1 -qopt-report-phase=vec myprog.c mysubroutines.c -o myprog.x
+ $ ifort -ipo -O3 -xCORE-AVX2 -qopt-report1 -qopt-report-phase=vec myprog.f mysubroutines.f -o myprog.x
+
+In this example, we compile the program enabling interprocedural
+optimizations between source files (-ipo), aggresive loop optimizations
+(-O3) and vectorization (-xCORE-AVX2)
+
+The compiler recognizes the omp, simd, vector and ivdep pragmas for
+OpenMP parallelization and AVX2 vectorization. Enable the OpenMP
+parallelization by the **-openmp** compiler switch.
+
+ $ icc -ipo -O3 -xCORE-AVX2 -qopt-report1 -qopt-report-phase=vec -openmp myprog.c mysubroutines.c -o myprog.x
+ $ ifort -ipo -O3 -xCORE-AVX2 -qopt-report1 -qopt-report-phase=vec -openmp myprog.f mysubroutines.f -o myprog.x
+
+Read more
+at <https://software.intel.com/en-us/intel-cplusplus-compiler-16.0-user-and-reference-guide>
+
+Sandy Bridge/Ivy Bridge/Haswell binary compatibility
+----------------------------------------------------
+
+Anselm nodes are currently equipped with Sandy Bridge CPUs, while
+Salomon compute nodes are equipped with Haswell based architecture. The
+UV1 SMP compute server has Ivy Bridge CPUs, which are equivalent to
+Sandy Bridge (only smaller manufacturing technology). >The new
+processors are backward compatible with the Sandy Bridge nodes, so all
+programs that ran on the Sandy Bridge processors, should also run on the
+new Haswell nodes. >To get optimal performance out of the
+Haswell processors a program should make use of the
+special >AVX2 instructions for this processor. One can do
+this by recompiling codes with the compiler
+flags >designated to invoke these instructions. For the
+Intel compiler suite, there are two ways of
+doing >this:
+
+- >Using compiler flag (both for Fortran and C):
+ -xCORE-AVX2. This will create a
+ binary class="s1">with AVX2 instructions, specifically
+ for the Haswell processors. Note that the
+ executable >will not run on Sandy Bridge/Ivy
+ Bridge nodes.
+- >Using compiler flags (both for Fortran and C):
+ -xAVX -axCORE-AVX2. This
+ will >generate multiple, feature specific auto-dispatch
+ code paths for Intel® processors, if there is >a
+ performance benefit. So this binary will run both on Sandy
+ Bridge/Ivy Bridge and Haswell >processors. During
+ runtime it will be decided which path to follow, dependent on
+ which >processor you are running on. In general this
+ will result in larger binaries.
+
diff --git a/converted/docs.it4i.cz/salomon/software/intel-suite/intel-debugger.md b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-debugger.md
new file mode 100644
index 0000000000000000000000000000000000000000..a806174fdc4f8b694b5db01a5582ed7e889b5831
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-debugger.md
@@ -0,0 +1,100 @@
+Intel Debugger
+==============
+
+
+
+IDB is no longer available since Intel Parallel Studio 2015
+
+Debugging serial applications
+-----------------------------
+
+The intel debugger version 13.0 is available, via module intel. The
+debugger works for applications compiled with C and C++ compiler and the
+ifort fortran 77/90/95 compiler. The debugger provides java GUI
+environment. Use [X
+display](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html)
+for running the GUI.
+
+ $ module load intel/2014.06
+ $ module load Java
+ $ idb
+
+The debugger may run in text mode. To debug in text mode, use
+
+ $ idbc
+
+To debug on the compute nodes, module intel must be loaded.
+The GUI on compute nodes may be accessed using the same way as in [the
+GUI
+section](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html)
+
+Example:
+
+ $ qsub -q qexp -l select=1:ncpus=24 -X -I
+ qsub: waiting for job 19654.srv11 to start
+ qsub: job 19654.srv11 ready
+
+ $ module load intel
+ $ module load Java
+ $ icc -O0 -g myprog.c -o myprog.x
+ $ idb ./myprog.x
+
+In this example, we allocate 1 full compute node, compile program
+myprog.c with debugging options -O0 -g and run the idb debugger
+interactively on the myprog.x executable. The GUI access is via X11 port
+forwarding provided by the PBS workload manager.
+
+Debugging parallel applications
+-------------------------------
+
+Intel debugger is capable of debugging multithreaded and MPI parallel
+programs as well.
+
+### Small number of MPI ranks
+
+For debugging small number of MPI ranks, you may execute and debug each
+rank in separate xterm terminal (do not forget the [X
+display](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html)).
+Using Intel MPI, this may be done in following way:
+
+ $ qsub -q qexp -l select=2:ncpus=24 -X -I
+ qsub: waiting for job 19654.srv11 to start
+ qsub: job 19655.srv11 ready
+
+ $ module load intel impi
+ $ mpirun -ppn 1 -hostfile $PBS_NODEFILE --enable-x xterm -e idbc ./mympiprog.x
+
+In this example, we allocate 2 full compute node, run xterm on each node
+and start idb debugger in command line mode, debugging two ranks of
+mympiprog.x application. The xterm will pop up for each rank, with idb
+prompt ready. The example is not limited to use of Intel MPI
+
+### Large number of MPI ranks
+
+Run the idb debugger from within the MPI debug option. This will cause
+the debugger to bind to all ranks and provide aggregated outputs across
+the ranks, pausing execution automatically just after startup. You may
+then set break points and step the execution manually. Using Intel MPI:
+
+ $ qsub -q qexp -l select=2:ncpus=24 -X -I
+ qsub: waiting for job 19654.srv11 to start
+ qsub: job 19655.srv11 ready
+
+ $ module load intel impi
+ $ mpirun -n 48 -idb ./mympiprog.x
+
+### Debugging multithreaded application
+
+Run the idb debugger in GUI mode. The menu Parallel contains number of
+tools for debugging multiple threads. One of the most useful tools is
+the **Serialize Execution** tool, which serializes execution of
+concurrent threads for easy orientation and identification of
+concurrency related bugs.
+
+Further information
+-------------------
+
+Exhaustive manual on idb features and usage is published at Intel
+website,
+<https://software.intel.com/sites/products/documentation/doclib/iss/2013/compiler/cpp-lin/>
+
diff --git a/converted/docs.it4i.cz/salomon/software/intel-suite/intel-inspector.md b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-inspector.md
new file mode 100644
index 0000000000000000000000000000000000000000..cfbde48083ddaa8cc5cc60a481e0278375177302
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+++ b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-inspector.md
@@ -0,0 +1,63 @@
+Intel Inspector
+===============
+
+Intel Inspector is a dynamic memory and threading error checking tool
+for C/C++/Fortran applications. It can detect issues such as memory
+leaks, invalid memory references, uninitalized variables, race
+conditions, deadlocks etc.
+
+Installed versions
+------------------
+
+The following versions are currently available on Salomon as modules:
+
+ --------- |---|---|---------------
+ |---|---|
+ |2016 Update 1|Inspector/2016_update1|
+ --------- |---|---|---------------
+
+Usage
+-----
+
+Your program should be compiled with -g switch to include symbol names.
+Optimizations can be turned on.
+
+Debugging is possible either directly from the GUI, or from command
+line.
+
+### GUI mode
+
+To debug from GUI, launch Inspector:
+
+ $ inspxe-gui &
+
+Then select menu File -> New -> Project. Choose a directory to
+save project data to. After clicking OK, Project properties window will
+appear, where you can configure path to your binary, launch arguments,
+working directory etc. After clicking OK, the project is ready.
+
+In the main pane, you can start a predefined analysis type or define
+your own. Click Start to start the analysis. Alternatively, you can
+click on Command Line, to see the command line required to run the
+analysis directly from command line.
+
+### Batch mode
+
+Analysis can be also run from command line in batch mode. Batch mode
+analysis is run with command inspxe-cl.
+To obtain the required parameters, either consult the documentation or
+you can configure the analysis in the GUI and then click "Command Line"
+button in the lower right corner to the respective command line.
+
+Results obtained from batch mode can be then viewed in the GUI by
+selecting File -> Open -> Result...
+
+References
+----------
+
+1. [Product
+ page](https://software.intel.com/en-us/intel-inspector-xe)
+2. [Documentation and Release
+ Notes](https://software.intel.com/en-us/intel-inspector-xe-support/documentation)
+3. [Tutorials](https://software.intel.com/en-us/articles/inspectorxe-tutorials)
+
diff --git a/converted/docs.it4i.cz/salomon/software/intel-suite/intel-integrated-performance-primitives.md b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-integrated-performance-primitives.md
new file mode 100644
index 0000000000000000000000000000000000000000..5ec3bf70b64bf35c2fdf3382bc0c354afe340941
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-integrated-performance-primitives.md
@@ -0,0 +1,94 @@
+Intel IPP
+=========
+
+
+
+Intel Integrated Performance Primitives
+---------------------------------------
+
+Intel Integrated Performance Primitives, version 9.0.1, compiled for
+AVX2 vector instructions is available, via module ipp. The IPP is a very
+rich library of highly optimized algorithmic building blocks for media
+and data applications. This includes signal, image and frame processing
+algorithms, such as FFT, FIR, Convolution, Optical Flow, Hough
+transform, Sum, MinMax, as well as cryptographic functions, linear
+algebra functions and many more.
+
+Check out IPP before implementing own math functions for data
+processing, it is likely already there.
+
+ $ module load ipp
+
+The module sets up environment variables, required for linking and
+running ipp enabled applications.
+
+IPP example
+-----------
+
+ #include "ipp.h"
+ #include <stdio.h>
+ int main(int argc, char* argv[])
+ {
+ const IppLibraryVersion *lib;
+ Ipp64u fm;
+ IppStatus status;
+
+ status= ippInit(); //IPP initialization with the best optimization layer
+ if( status != ippStsNoErr ) {
+ printf("IppInit() Error:n");
+ printf("%sn", ippGetStatusString(status) );
+ return -1;
+ }
+
+ //Get version info
+ lib = ippiGetLibVersion();
+ printf("%s %sn", lib->Name, lib->Version);
+
+ //Get CPU features enabled with selected library level
+ fm=ippGetEnabledCpuFeatures();
+ printf("SSE :%cn",(fm>1)&1?'Y':'N');
+ printf("SSE2 :%cn",(fm>2)&1?'Y':'N');
+ printf("SSE3 :%cn",(fm>3)&1?'Y':'N');
+ printf("SSSE3 :%cn",(fm>4)&1?'Y':'N');
+ printf("SSE41 :%cn",(fm>6)&1?'Y':'N');
+ printf("SSE42 :%cn",(fm>7)&1?'Y':'N');
+ printf("AVX :%cn",(fm>8)&1 ?'Y':'N');
+ printf("AVX2 :%cn", (fm>15)&1 ?'Y':'N' );
+ printf("----------n");
+ printf("OS Enabled AVX :%cn", (fm>9)&1 ?'Y':'N');
+ printf("AES :%cn", (fm>10)&1?'Y':'N');
+ printf("CLMUL :%cn", (fm>11)&1?'Y':'N');
+ printf("RDRAND :%cn", (fm>13)&1?'Y':'N');
+ printf("F16C :%cn", (fm>14)&1?'Y':'N');
+
+ return 0;
+ }
+
+Â Compile above example, using any compiler and the ipp module.
+
+ $ module load intel
+ $ module load ipp
+
+ $ icc testipp.c -o testipp.x -lippi -lipps -lippcore
+
+You will need the ipp module loaded to run the ipp enabled executable.
+This may be avoided, by compiling library search paths into the
+executable
+
+ $ module load intel
+ $ module load ipp
+
+ $ icc testipp.c -o testipp.x -Wl,-rpath=$LIBRARY_PATH -lippi -lipps -lippcore
+
+Code samples and documentation
+------------------------------
+
+Intel provides number of [Code Samples for
+IPP](https://software.intel.com/en-us/articles/code-samples-for-intel-integrated-performance-primitives-library),
+illustrating use of IPP.
+
+Read full documentation on IPP [on Intel
+website,](http://software.intel.com/sites/products/search/search.php?q=&x=15&y=6&product=ipp&version=7.1&docos=lin)
+in particular the [IPP Reference
+manual.](http://software.intel.com/sites/products/documentation/doclib/ipp_sa/71/ipp_manual/index.htm)
+
diff --git a/converted/docs.it4i.cz/salomon/software/intel-suite/intel-mkl.md b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-mkl.md
new file mode 100644
index 0000000000000000000000000000000000000000..57711b34ae2797e4040aa04a62ce81c096be5d6e
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-mkl.md
@@ -0,0 +1,200 @@
+Intel MKL
+=========
+
+
+
+Intel Math Kernel Library
+-------------------------
+
+Intel Math Kernel Library (Intel MKL) is a library of math kernel
+subroutines, extensively threaded and optimized for maximum performance.
+Intel MKL provides these basic math kernels:
+
+-
+
+
+
+ BLAS (level 1, 2, and 3) and LAPACK linear algebra routines,
+ offering vector, vector-matrix, and matrix-matrix operations.
+-
+
+
+
+ The PARDISO direct sparse solver, an iterative sparse solver,
+ and supporting sparse BLAS (level 1, 2, and 3) routines for solving
+ sparse systems of equations.
+-
+
+
+
+ ScaLAPACK distributed processing linear algebra routines for
+ Linux* and Windows* operating systems, as well as the Basic Linear
+ Algebra Communications Subprograms (BLACS) and the Parallel Basic
+ Linear Algebra Subprograms (PBLAS).
+-
+
+
+
+ Fast Fourier transform (FFT) functions in one, two, or three
+ dimensions with support for mixed radices (not limited to sizes that
+ are powers of 2), as well as distributed versions of
+ these functions.
+-
+
+
+
+ Vector Math Library (VML) routines for optimized mathematical
+ operations on vectors.
+-
+
+
+
+ Vector Statistical Library (VSL) routines, which offer
+ high-performance vectorized random number generators (RNG) for
+ several probability distributions, convolution and correlation
+ routines, and summary statistics functions.
+-
+
+
+
+ Data Fitting Library, which provides capabilities for
+ spline-based approximation of functions, derivatives and integrals
+ of functions, and search.
+- Extended Eigensolver, a shared memory version of an eigensolver
+ based on the Feast Eigenvalue Solver.
+
+For details see the [Intel MKL Reference
+Manual](http://software.intel.com/sites/products/documentation/doclib/mkl_sa/11/mklman/index.htm).
+
+Intel MKL version 11.2.3.187 is available on the cluster
+
+ $ module load imkl
+
+The module sets up environment variables, required for linking and
+running mkl enabled applications. The most important variables are the
+$MKLROOT, $CPATH, $LD_LIBRARY_PATH and $MKL_EXAMPLES
+
+Intel MKL library may be linked using any compiler.
+With intel compiler use -mkl option to link default threaded MKL.
+
+### Interfaces
+
+Intel MKL library provides number of interfaces. The fundamental once
+are the LP64 and ILP64. The Intel MKL ILP64 libraries use the 64-bit
+integer type (necessary for indexing large arrays, with more than
+231^-1 elements), whereas the LP64 libraries index arrays with the
+32-bit integer type.
+
+ |Interface|Integer type|
+ ----- |---|---|-------------------------------------
+ |LP64|32-bit, int, integer(kind=4), MPI_INT|
+ ILP64 64-bit, long int, integer(kind=8), MPI_INT64
+
+### Linking
+
+Linking Intel MKL libraries may be complex. Intel [mkl link line
+advisor](http://software.intel.com/en-us/articles/intel-mkl-link-line-advisor)
+helps. See also [examples](intel-mkl.html#examples) below.
+
+You will need the mkl module loaded to run the mkl enabled executable.
+This may be avoided, by compiling library search paths into the
+executable. Include rpath on the compile line:
+
+ $ icc .... -Wl,-rpath=$LIBRARY_PATH ...
+
+### Threading
+
+Advantage in using Intel MKL library is that it brings threaded
+parallelization to applications that are otherwise not parallel.
+
+For this to work, the application must link the threaded MKL library
+(default). Number and behaviour of MKL threads may be controlled via the
+OpenMP environment variables, such as OMP_NUM_THREADS and
+KMP_AFFINITY. MKL_NUM_THREADS takes precedence over OMP_NUM_THREADS
+
+ $ export OMP_NUM_THREADS=24
+ $ export KMP_AFFINITY=granularity=fine,compact,1,0
+
+The application will run with 24 threads with affinity optimized for
+fine grain parallelization.
+
+Examples
+------------
+
+Number of examples, demonstrating use of the Intel MKL library and its
+linking is available on clusters, in the $MKL_EXAMPLES directory. In
+the examples below, we demonstrate linking Intel MKL to Intel and GNU
+compiled program for multi-threaded matrix multiplication.
+
+### Working with examples
+
+ $ module load intel
+ $ module load imkl
+ $ cp -a $MKL_EXAMPLES/cblas /tmp/
+ $ cd /tmp/cblas
+
+ $ make sointel64 function=cblas_dgemm
+
+In this example, we compile, link and run the cblas_dgemm example,
+demonstrating use of MKL example suite installed on clusters.
+
+### Example: MKL and Intel compiler
+
+ $ module load intel
+ $ module load imkl
+ $ cp -a $MKL_EXAMPLES/cblas /tmp/
+ $ cd /tmp/cblas
+ $
+ $ icc -w source/cblas_dgemmx.c source/common_func.c -mkl -o cblas_dgemmx.x
+ $ ./cblas_dgemmx.x data/cblas_dgemmx.d
+
+In this example, we compile, link and run the cblas_dgemm example,
+demonstrating use of MKL with icc -mkl option. Using the -mkl option is
+equivalent to:
+
+ $ icc -w source/cblas_dgemmx.c source/common_func.c -o cblas_dgemmx.x
+ -I$MKL_INC_DIR -L$MKL_LIB_DIR -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -liomp5
+
+In this example, we compile and link the cblas_dgemm example, using
+LP64 interface to threaded MKL and Intel OMP threads implementation.
+
+### Example: Intel MKL and GNU compiler
+
+ $ module load GCC
+ $ module load imkl
+ $ cp -a $MKL_EXAMPLES/cblas /tmp/
+ $ cd /tmp/cblas
+
+ $ gcc -w source/cblas_dgemmx.c source/common_func.c -o cblas_dgemmx.x
+ -lmkl_intel_lp64 -lmkl_gnu_thread -lmkl_core -lgomp -lm
+
+ $ ./cblas_dgemmx.x data/cblas_dgemmx.d
+
+In this example, we compile, link and run the cblas_dgemm example,
+using LP64 interface to threaded MKL and gnu OMP threads implementation.
+
+MKL and MIC accelerators
+------------------------
+
+The Intel MKL is capable to automatically offload the computations o the
+MIC accelerator. See section [Intel Xeon
+Phi](../intel-xeon-phi.html) for details.
+
+LAPACKE C Interface
+-------------------
+
+MKL includes LAPACKE C Interface to LAPACK. For some reason, although
+Intel is the author of LAPACKE, the LAPACKE header files are not present
+in MKL. For this reason, we have prepared
+LAPACKE module, which includes Intel's LAPACKE
+headers from official LAPACK, which you can use to compile code using
+LAPACKE interface against MKL.
+
+Further reading
+---------------
+
+Read more on [Intel
+website](http://software.intel.com/en-us/intel-mkl), in
+particular the [MKL users
+guide](https://software.intel.com/en-us/intel-mkl/documentation/linux).
+
diff --git a/converted/docs.it4i.cz/salomon/software/intel-suite/intel-parallel-studio-introduction.md b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-parallel-studio-introduction.md
new file mode 100644
index 0000000000000000000000000000000000000000..d77b2d908e90cb53d38269d3e3094a3d6c43e3c8
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-parallel-studio-introduction.md
@@ -0,0 +1,95 @@
+Intel Parallel Studio
+=====================
+
+
+
+The Salomon cluster provides following elements of the Intel Parallel
+Studio XE
+
+ Intel Parallel Studio XE
+ -------------------------------------------------
+ Intel Compilers
+ Intel Debugger
+ Intel MKL Library
+ Intel Integrated Performance Primitives Library
+ Intel Threading Building Blocks Library
+ Intel Trace Analyzer and Collector
+ Intel Advisor
+ Intel Inspector
+
+Intel compilers
+---------------
+
+The Intel compilers version 131.3 are available, via module
+iccifort/2013.5.192-GCC-4.8.3. The compilers include the icc C and C++
+compiler and the ifort fortran 77/90/95 compiler.
+
+ $ module load intel
+ $ icc -v
+ $ ifort -v
+
+Read more at the [Intel Compilers](intel-compilers.html)
+page.
+
+Intel debugger
+--------------
+
+IDB is no longer available since Parallel Studio 2015.
+
+Â The intel debugger version 13.0 is available, via module intel. The
+debugger works for applications compiled with C and C++ compiler and the
+ifort fortran 77/90/95 compiler. The debugger provides java GUI
+environment. Use [X
+display](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html)
+for running the GUI.
+
+ $ module load intel
+ $ idb
+
+Read more at the [Intel Debugger](intel-debugger.html)
+page.
+
+Intel Math Kernel Library
+-------------------------
+
+Intel Math Kernel Library (Intel MKL) is a library of math kernel
+subroutines, extensively threaded and optimized for maximum performance.
+Intel MKL unites and provides these basic components: BLAS, LAPACK,
+ScaLapack, PARDISO, FFT, VML, VSL, Data fitting, Feast Eigensolver and
+many more.
+
+ $ module load imkl
+
+Read more at the [Intel MKL](intel-mkl.html) page.
+
+Intel Integrated Performance Primitives
+---------------------------------------
+
+Intel Integrated Performance Primitives, version 7.1.1, compiled for AVX
+is available, via module ipp. The IPP is a library of highly optimized
+algorithmic building blocks for media and data applications. This
+includes signal, image and frame processing algorithms, such as FFT,
+FIR, Convolution, Optical Flow, Hough transform, Sum, MinMax and many
+more.
+
+ $ module load ipp
+
+Read more at the [Intel
+IPP](intel-integrated-performance-primitives.html) page.
+
+Intel Threading Building Blocks
+-------------------------------
+
+Intel Threading Building Blocks (Intel TBB) is a library that supports
+scalable parallel programming using standard ISO C++ code. It does not
+require special languages or compilers. It is designed to promote
+scalable data parallel programming. Additionally, it fully supports
+nested parallelism, so you can build larger parallel components from
+smaller parallel components. To use the library, you specify tasks, not
+threads, and let the library map tasks onto threads in an efficient
+manner.
+
+ $ module load tbb
+
+Read more at the [Intel TBB](intel-tbb.html) page.
+
diff --git a/converted/docs.it4i.cz/salomon/software/intel-suite/intel-tbb.md b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-tbb.md
new file mode 100644
index 0000000000000000000000000000000000000000..8fea59c78cccd8be49c2d21e0e18f89ba0e1b2ea
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-tbb.md
@@ -0,0 +1,54 @@
+Intel TBB
+=========
+
+
+
+Intel Threading Building Blocks
+-------------------------------
+
+Intel Threading Building Blocks (Intel TBB) is a library that supports
+scalable parallel programming using standard ISO C++ code. It does not
+require special languages or compilers. To use the library, you specify
+tasks, not threads, and let the library map tasks onto threads in an
+efficient manner. The tasks are executed by a runtime scheduler and may
+be offloaded to [MIC
+accelerator](../intel-xeon-phi.html).
+
+Intel TBB version 4.3.5.187 is available on the cluster.
+
+ $ module load tbb
+
+The module sets up environment variables, required for linking and
+running tbb enabled applications.
+
+Link the tbb library, using -ltbb
+
+Examples
+--------
+
+Number of examples, demonstrating use of TBB and its built-in schedulerÂ
+is available on Anselm, in the $TBB_EXAMPLES directory.
+
+ $ module load intel
+ $ module load tbb
+ $ cp -a $TBB_EXAMPLES/common $TBB_EXAMPLES/parallel_reduce /tmp/
+ $ cd /tmp/parallel_reduce/primes
+ $ icc -O2 -DNDEBUG -o primes.x main.cpp primes.cpp -ltbb
+ $ ./primes.x
+
+In this example, we compile, link and run the primes example,
+demonstrating use of parallel task-based reduce in computation of prime
+numbers.
+
+You will need the tbb module loaded to run the tbb enabled executable.
+This may be avoided, by compiling library search paths into the
+executable.
+
+ $ icc -O2 -o primes.x main.cpp primes.cpp -Wl,-rpath=$LIBRARY_PATH -ltbb
+
+Further reading
+---------------
+
+Read more on Intel website,
+<http://software.intel.com/sites/products/documentation/doclib/tbb_sa/help/index.htm>
+
diff --git a/converted/docs.it4i.cz/salomon/software/intel-suite/intel-trace-analyzer-and-collector.md b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-trace-analyzer-and-collector.md
new file mode 100644
index 0000000000000000000000000000000000000000..510aae8b64321e4fbdb8f769730d4fa92552b81b
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/intel-suite/intel-trace-analyzer-and-collector.md
@@ -0,0 +1,54 @@
+Intel Trace Analyzer and Collector
+==================================
+
+Intel Trace Analyzer and Collector (ITAC) is a tool to collect and
+graphicaly analyze behaviour of MPI applications. It helps you to
+analyze communication patterns of your application, identify hotspots,
+perform correctnes checking (identify deadlocks, data corruption etc),
+simulate how your application would run on a different interconnect.Â
+
+ITAC is a offline analysis tool - first you run your application to
+collect a trace file, then you can open the trace in a GUI analyzer to
+view it.
+
+Installed version
+-----------------
+
+Currently on Salomon is version 9.1.2.024 available as moduleÂ
+itac/9.1.2.024
+
+Collecting traces
+-----------------
+
+ITAC can collect traces from applications that are using Intel MPI. To
+generate a trace, simply add -trace option to your mpirun command :
+
+ $ module load itac/9.1.2.024
+ $ mpirun -trace myapp
+
+The trace will be saved in file myapp.stf in the current directory.
+
+Viewing traces
+--------------
+
+To view and analyze the trace, open ITAC GUI in a [graphical
+environment](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html)
+:
+
+ $ module load itac/9.1.2.024
+ $ traceanalyzer
+
+The GUI will launch and you can open the produced *.stf file.
+
+
+
+Please refer to Intel documenation about usage of the GUI tool.
+
+References
+----------
+
+1. [Getting Started with Intel® Trace Analyzer and
+ Collector](https://software.intel.com/en-us/get-started-with-itac-for-linux)
+2. [Intel® Trace Analyzer and Collector -
+ Documentation](http://Intel®%20Trace%20Analyzer%20and%20Collector%20-%20Documentation)
+
diff --git a/converted/docs.it4i.cz/salomon/software/intel-xeon-phi.md b/converted/docs.it4i.cz/salomon/software/intel-xeon-phi.md
new file mode 100644
index 0000000000000000000000000000000000000000..55e70e7577678526a8a1fb197ac915527ff85895
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/intel-xeon-phi.md
@@ -0,0 +1,1062 @@
+Intel Xeon Phi
+==============
+
+A guide to Intel Xeon Phi usage
+
+
+
+Intel Xeon Phi accelerator can be programmed in several modes. The
+default mode on the cluster is offload mode, but all modes described in
+this document are supported.
+
+Intel Utilities for Xeon Phi
+----------------------------
+
+To get access to a compute node with Intel Xeon Phi accelerator, use the
+PBS interactive session
+
+ $ qsub -I -q qprod -l select=1:ncpus=24:accelerator=True:naccelerators=2:accelerator_model=phi7120 -A NONE-0-0
+
+To set up the environment module "intel" has to be loaded, without
+specifying the version, default version is loaded (at time of writing
+this, it's 2015b)
+
+ $ module load intel
+
+Information about the hardware can be obtained by running
+the micinfo program on the host.
+
+ $ /usr/bin/micinfo
+
+The output of the "micinfo" utility executed on one of the cluster node
+is as follows. (note: to get PCIe related details the command has to be
+run with root privileges)
+
+ MicInfo Utility Log
+ Created Mon Aug 17 13:55:59 2015
+
+ System Info
+ HOST OS : Linux
+ OS Version : 2.6.32-504.16.2.el6.x86_64
+ Driver Version : 3.4.1-1
+ MPSS Version : 3.4.1
+ Host Physical Memory : 131930 MB
+
+ Device No: 0, Device Name: mic0
+
+ Version
+ Flash Version : 2.1.02.0390
+ SMC Firmware Version : 1.16.5078
+ SMC Boot Loader Version : 1.8.4326
+ uOS Version : 2.6.38.8+mpss3.4.1
+ Device Serial Number : ADKC44601414
+
+ Board
+ Vendor ID : 0x8086
+ Device ID : 0x225c
+ Subsystem ID : 0x7d95
+ Coprocessor Stepping ID : 2
+ PCIe Width : x16
+ PCIe Speed : 5 GT/s
+ PCIe Max payload size : 256 bytes
+ PCIe Max read req size : 512 bytes
+ Coprocessor Model : 0x01
+ Coprocessor Model Ext : 0x00
+ Coprocessor Type : 0x00
+ Coprocessor Family : 0x0b
+ Coprocessor Family Ext : 0x00
+ Coprocessor Stepping : C0
+ Board SKU : C0PRQ-7120 P/A/X/D
+ ECC Mode : Enabled
+ SMC HW Revision : Product 300W Passive CS
+
+ Cores
+ Total No of Active Cores : 61
+ Voltage : 1007000 uV
+ Frequency : 1238095 kHz
+
+ Thermal
+ Fan Speed Control : N/A
+ Fan RPM : N/A
+ Fan PWM : N/A
+ Die Temp : 60 C
+
+ GDDR
+ GDDR Vendor : Samsung
+ GDDR Version : 0x6
+ GDDR Density : 4096 Mb
+ GDDR Size : 15872 MB
+ GDDR Technology : GDDR5
+ GDDR Speed : 5.500000 GT/s
+ GDDR Frequency : 2750000 kHz
+ GDDR Voltage : 1501000 uV
+
+ Device No: 1, Device Name: mic1
+
+ Version
+ Flash Version : 2.1.02.0390
+ SMC Firmware Version : 1.16.5078
+ SMC Boot Loader Version : 1.8.4326
+ uOS Version : 2.6.38.8+mpss3.4.1
+ Device Serial Number : ADKC44500454
+
+ Board
+ Vendor ID : 0x8086
+ Device ID : 0x225c
+ Subsystem ID : 0x7d95
+ Coprocessor Stepping ID : 2
+ PCIe Width : x16
+ PCIe Speed : 5 GT/s
+ PCIe Max payload size : 256 bytes
+ PCIe Max read req size : 512 bytes
+ Coprocessor Model : 0x01
+ Coprocessor Model Ext : 0x00
+ Coprocessor Type : 0x00
+ Coprocessor Family : 0x0b
+ Coprocessor Family Ext : 0x00
+ Coprocessor Stepping : C0
+ Board SKU : C0PRQ-7120 P/A/X/D
+ ECC Mode : Enabled
+ SMC HW Revision : Product 300W Passive CS
+
+ Cores
+ Total No of Active Cores : 61
+ Voltage : 998000 uV
+ Frequency : 1238095 kHz
+
+ Thermal
+ Fan Speed Control : N/A
+ Fan RPM : N/A
+ Fan PWM : N/A
+ Die Temp : 59 C
+
+ GDDR
+ GDDR Vendor : Samsung
+ GDDR Version : 0x6
+ GDDR Density : 4096 Mb
+ GDDR Size : 15872 MB
+ GDDR Technology : GDDR5
+ GDDR Speed : 5.500000 GT/s
+ GDDR Frequency : 2750000 kHz
+ GDDR Voltage : 1501000 uV
+
+Offload Mode
+------------
+
+To compile a code for Intel Xeon Phi a MPSS stack has to be installed on
+the machine where compilation is executed. Currently the MPSS stack is
+only installed on compute nodes equipped with accelerators.
+
+ $ qsub -I -q qprod -l select=1:ncpus=24:accelerator=True:naccelerators=2:accelerator_model=phi7120 -A NONE-0-0
+ $ module load intel
+
+For debugging purposes it is also recommended to set environment
+variable "OFFLOAD_REPORT". Value can be set from 0 to 3, where higher
+number means more debugging information.
+
+ export OFFLOAD_REPORT=3
+
+A very basic example of code that employs offload programming technique
+is shown in the next listing. Please note that this code is sequential
+and utilizes only single core of the accelerator.
+
+ $ vim source-offload.cpp
+
+ #include <iostream>
+
+ int main(int argc, char* argv[])
+ {
+ Â Â Â const int niter = 100000;
+ Â Â Â double result = 0;
+
+ Â #pragma offload target(mic)
+ Â Â Â for (int i = 0; i < niter; ++i) {
+ Â Â Â Â Â Â Â const double t = (i + 0.5) / niter;
+ Â Â Â Â Â Â Â result += 4.0 / (t * t + 1.0);
+ Â Â Â }
+ Â Â Â result /= niter;
+ Â Â Â std::cout << "Pi ~ " << result << 'n';
+ }
+
+To compile a code using Intel compiler run
+
+ $ icc source-offload.cpp -o bin-offload
+
+To execute the code, run the following command on the host
+
+ ./bin-offload
+
+### Parallelization in Offload Mode Using OpenMP
+
+One way of paralelization a code for Xeon Phi is using OpenMP
+directives. The following example shows code for parallel vector
+addition.Â
+
+ $ vim ./vect-add
+
+ #include <stdio.h>
+
+ typedef int T;
+
+ #define SIZE 1000
+
+ #pragma offload_attribute(push, target(mic))
+ T in1[SIZE];
+ T in2[SIZE];
+ T res[SIZE];
+ #pragma offload_attribute(pop)
+
+ // MIC function to add two vectors
+ __attribute__((target(mic))) add_mic(T *a, T *b, T *c, int size) {
+ Â int i = 0;
+ Â #pragma omp parallel for
+ Â Â Â for (i = 0; i < size; i++)
+ Â Â Â Â Â c[i] = a[i] + b[i];
+ }
+
+ // CPU function to add two vectors
+ void add_cpu (T *a, T *b, T *c, int size) {
+ Â int i;
+ Â for (i = 0; i < size; i++)
+ Â Â Â c[i] = a[i] + b[i];
+ }
+
+ // CPU function to generate a vector of random numbers
+ void random_T (T *a, int size) {
+ Â int i;
+ Â for (i = 0; i < size; i++)
+ Â Â Â a[i] = rand() % 10000; // random number between 0 and 9999
+ }
+
+ // CPU function to compare two vectors
+ int compare(T *a, T *b, T size ){
+ Â int pass = 0;
+ Â int i;
+ Â for (i = 0; i < size; i++){
+ Â Â Â if (a[i] != b[i]) {
+ Â Â Â Â Â printf("Value mismatch at location %d, values %d and %dn",i, a[i], b[i]);
+ Â Â Â Â Â pass = 1;
+ Â Â Â }
+ Â }
+ Â if (pass == 0) printf ("Test passedn"); else printf ("Test Failedn");
+ Â return pass;
+ }
+
+ int main()
+ {
+ Â int i;
+ Â random_T(in1, SIZE);
+ Â random_T(in2, SIZE);
+
+ Â #pragma offload target(mic) in(in1,in2)Â inout(res)
+ Â {
+
+ Â Â Â // Parallel loop from main function
+ Â Â Â #pragma omp parallel for
+ Â Â Â for (i=0; i<SIZE; i++)
+ Â Â Â Â Â res[i] = in1[i] + in2[i];
+
+ Â Â Â // or parallel loop is called inside the function
+ Â Â Â add_mic(in1, in2, res, SIZE);
+
+ Â }
+
+ Â //Check the results with CPU implementation
+ Â T res_cpu[SIZE];
+ Â add_cpu(in1, in2, res_cpu, SIZE);
+ Â compare(res, res_cpu, SIZE);
+
+ }
+
+During the compilation Intel compiler shows which loops have been
+vectorized in both host and accelerator. This can be enabled with
+compiler option "-vec-report2". To compile and execute the code run
+
+ $ icc vect-add.c -openmp_report2 -vec-report2 -o vect-add
+
+ $ ./vect-add
+
+Some interesting compiler flags useful not only for code debugging are:
+
+Debugging
+Â openmp_report[0|1|2] - controls the compiler based vectorization
+diagnostic level
+Â vec-report[0|1|2] - controls the OpenMP parallelizer diagnostic
+level
+
+Performance ooptimization
+Â xhost - FOR HOST ONLY - to generate AVX (Advanced Vector Extensions)
+instructions.
+
+Automatic Offload using Intel MKL Library
+-----------------------------------------
+
+Intel MKL includes an Automatic Offload (AO) feature that enables
+computationally intensive MKL functions called in user code to benefit
+from attached Intel Xeon Phi coprocessors automatically and
+transparently.
+
+Behavioural of automatic offload mode is controlled by functions called
+within the program or by environmental variables. Complete list of
+controls is listed [
+here](http://software.intel.com/sites/products/documentation/doclib/mkl_sa/11/mkl_userguide_lnx/GUID-3DC4FC7D-A1E4-423D-9C0C-06AB265FFA86.htm).
+
+The Automatic Offload may be enabled by either an MKL function call
+within the code:
+
+ mkl_mic_enable();
+
+or by setting environment variable
+
+ $ export MKL_MIC_ENABLE=1
+
+To get more information about automatic offload please refer to "[Using
+Intel® MKL Automatic Offload on Intel ® Xeon Phi™
+Coprocessors](http://software.intel.com/sites/default/files/11MIC42_How_to_Use_MKL_Automatic_Offload_0.pdf)"
+white paper or [ Intel MKL
+documentation](https://software.intel.com/en-us/articles/intel-math-kernel-library-documentation).
+
+### Automatic offload example #1
+
+Following example show how to automatically offload an SGEMM (single
+precision - g dir="auto">eneral matrix multiply) function to
+MIC coprocessor.
+
+At first get an interactive PBS session on a node with MIC accelerator
+and load "intel" module that automatically loads "mkl" module as well.
+
+ $ qsub -I -q qprod -l select=1:ncpus=24:accelerator=True:naccelerators=2:accelerator_model=phi7120 -A NONE-0-0
+ $ module load intel
+
+Â The code can be copied to a file and compiled without any necessary
+modification.Â
+
+ $ vim sgemm-ao-short.c
+
+`
+#include <stdio.h>
+#include <stdlib.h>
+#include <malloc.h>
+#include <stdint.h>
+
+#include "mkl.h"
+
+int main(int argc, char **argv)
+{
+Â Â Â Â Â Â Â float *A, *B, *C; /* Matrices */
+
+Â Â Â Â Â Â Â MKL_INT N = 2560; /* Matrix dimensions */
+Â Â Â Â Â Â Â MKL_INT LD = N; /* Leading dimension */
+Â Â Â Â Â Â Â int matrix_bytes; /* Matrix size in bytes */
+Â Â Â Â Â Â Â int matrix_elements; /* Matrix size in elements */
+
+Â Â Â Â Â Â Â float alpha = 1.0, beta = 1.0; /* Scaling factors */
+Â Â Â Â Â Â Â char transa = 'N', transb = 'N'; /* Transposition options */
+
+Â Â Â Â Â Â Â int i, j; /* Counters */
+
+Â Â Â Â Â Â Â matrix_elements = N * N;
+Â Â Â Â Â Â Â matrix_bytes = sizeof(float) * matrix_elements;
+
+Â Â Â Â Â Â Â /* Allocate the matrices */
+Â Â Â Â Â Â Â A = malloc(matrix_bytes); B = malloc(matrix_bytes); C = malloc(matrix_bytes);
+
+Â Â Â Â Â Â Â /* Initialize the matrices */
+Â Â Â Â Â Â Â for (i = 0; i < matrix_elements; i++) {
+Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â A[i] = 1.0; B[i] = 2.0; C[i] = 0.0;
+Â Â Â Â Â Â Â }
+
+Â Â Â Â Â Â Â printf("Computing SGEMM on the hostn");
+Â Â Â Â Â Â Â sgemm(&transa, &transb, &N, &N, &N, &alpha, A, &N, B, &N, &beta, C, &N);
+
+Â Â Â Â Â Â Â printf("Enabling Automatic Offloadn");
+Â Â Â Â Â Â Â /* Alternatively, set environment variable MKL_MIC_ENABLE=1 */
+Â Â Â Â Â Â Â mkl_mic_enable();
+Â Â Â Â Â Â Â
+Â Â Â Â Â Â Â int ndevices = mkl_mic_get_device_count(); /* Number of MIC devices */
+       printf("Automatic Offload enabled: %d MIC devices presentn",  ndevices);
+
+Â Â Â Â Â Â Â printf("Computing SGEMM with automatic workdivisionn");
+Â Â Â Â Â Â Â sgemm(&transa, &transb, &N, &N, &N, &alpha, A, &N, B, &N, &beta, C, &N);
+
+Â Â Â Â Â Â Â /* Free the matrix memory */
+Â Â Â Â Â Â Â free(A); free(B); free(C);
+
+Â Â Â Â Â Â Â printf("Donen");
+
+Â Â Â return 0;
+}
+`
+
+Please note: This example is simplified version of an example from MKL.
+The expanded version can be found here:
+$MKL_EXAMPLES/mic_ao/blasc/source/sgemm.c**
+
+To compile a code using Intel compiler use:
+
+ $ icc -mkl sgemm-ao-short.c -o sgemm
+
+For debugging purposes enable the offload report to see more information
+about automatic offloading.
+
+ $ export OFFLOAD_REPORT=2
+
+The output of a code should look similar to following listing, where
+lines starting with [MKL] are generated by offload reporting:
+
+ [user@r31u03n799 ~]$ ./sgemm
+ Computing SGEMM on the host
+ Enabling Automatic Offload
+ Automatic Offload enabled: 2 MIC devices present
+ Computing SGEMM with automatic workdivision
+ [MKL] [MIC --] [AO Function]Â Â Â SGEMM
+ [MKL] [MIC --] [AO SGEMM Workdivision]Â Â Â 0.44 0.28 0.28
+ [MKL] [MIC 00] [AO SGEMM CPU Time]Â Â Â 0.252427 seconds
+ [MKL] [MIC 00] [AO SGEMM MIC Time]Â Â Â 0.091001 seconds
+ [MKL] [MIC 00] [AO SGEMM CPU->MIC Data]Â Â Â 34078720 bytes
+ [MKL] [MIC 00] [AO SGEMM MIC->CPU Data]Â Â Â 7864320 bytes
+ [MKL] [MIC 01] [AO SGEMM CPU Time]Â Â Â 0.252427 seconds
+ [MKL] [MIC 01] [AO SGEMM MIC Time]Â Â Â 0.094758 seconds
+ [MKL] [MIC 01] [AO SGEMM CPU->MIC Data]Â Â Â 34078720 bytes
+ [MKL] [MIC 01] [AO SGEMM MIC->CPU Data]Â Â Â 7864320 bytes
+ Done
+
+Behavioral of automatic offload mode is controlled by functions called
+within the program or by environmental variables. Complete list of
+controls is listed [
+here](http://software.intel.com/sites/products/documentation/doclib/mkl_sa/11/mkl_userguide_lnx/GUID-3DC4FC7D-A1E4-423D-9C0C-06AB265FFA86.htm).
+
+To get more information about automatic offload please refer to "[Using
+Intel® MKL Automatic Offload on Intel ® Xeon Phi™
+Coprocessors](http://software.intel.com/sites/default/files/11MIC42_How_to_Use_MKL_Automatic_Offload_0.pdf)"
+white paper or [ Intel MKL
+documentation](https://software.intel.com/en-us/articles/intel-math-kernel-library-documentation).
+
+### Automatic offload example #2
+
+In this example, we will demonstrate automatic offload control via an
+environment vatiable MKL_MIC_ENABLE. The function DGEMM will be
+offloaded.
+
+At first get an interactive PBS session on a node with MIC accelerator.
+
+ $ qsub -I -q qprod -l select=1:ncpus=24:accelerator=True:naccelerators=2:accelerator_model=phi7120 -A NONE-0-0
+
+Once in, we enable the offload and run the Octave software. In octave,
+we generate two large random matrices and let them multiply together.
+
+ $ export MKL_MIC_ENABLE=1
+ $ export OFFLOAD_REPORT=2
+ $ module load Octave/3.8.2-intel-2015b
+
+ $ octave -q
+ octave:1> A=rand(10000);
+ octave:2> B=rand(10000);
+ octave:3> C=A*B;
+ [MKL] [MIC --] [AO Function]Â Â Â DGEMM
+ [MKL] [MIC --] [AO DGEMM Workdivision]Â Â Â 0.14 0.43 0.43
+ [MKL] [MIC 00] [AO DGEMM CPU Time]Â Â Â 3.814714 seconds
+ [MKL] [MIC 00] [AO DGEMM MIC Time]Â Â Â 2.781595 seconds
+ [MKL] [MIC 00] [AO DGEMM CPU->MIC Data]Â Â Â 1145600000 bytes
+ [MKL] [MIC 00] [AO DGEMM MIC->CPU Data]Â Â Â 1382400000 bytes
+ [MKL] [MIC 01] [AO DGEMM CPU Time]Â Â Â 3.814714 seconds
+ [MKL] [MIC 01] [AO DGEMM MIC Time]Â Â Â 2.843016 seconds
+ [MKL] [MIC 01] [AO DGEMM CPU->MIC Data]Â Â Â 1145600000 bytes
+ [MKL] [MIC 01] [AO DGEMM MIC->CPU Data]Â Â Â 1382400000 bytes
+ octave:4> exit
+
+On the example above we observe, that the DGEMM function workload was
+split over CPU, MIC 0 and MIC 1, in the ratio 0.14 0.43 0.43. The matrix
+multiplication was done on the CPU, accelerated by two Xeon Phi
+accelerators.
+
+Native Mode
+-----------
+
+In the native mode a program is executed directly on Intel Xeon Phi
+without involvement of the host machine. Similarly to offload mode, the
+code is compiled on the host computer with Intel compilers.
+
+To compile a code user has to be connected to a compute with MIC and
+load Intel compilers module. To get an interactive session on a compute
+node with an Intel Xeon Phi and load the module use following commands:Â
+
+ $ qsub -I -q qprod -l select=1:ncpus=24:accelerator=True:naccelerators=2:accelerator_model=phi7120 -A NONE-0-0
+
+ $ module load intel
+
+Please note that particular version of the Intel module is specified.
+This information is used later to specify the correct library paths.
+
+To produce a binary compatible with Intel Xeon Phi architecture user has
+to specify "-mmic" compiler flag. Two compilation examples are shown
+below. The first example shows how to compile OpenMP parallel code
+"vect-add.c" for host only:
+
+ $ icc -xhost -no-offload -fopenmp vect-add.c -o vect-add-host
+
+To run this code on host, use:
+
+ $ ./vect-add-host
+
+The second example shows how to compile the same code for Intel Xeon
+Phi:
+
+ $ icc -mmic -fopenmp vect-add.c -o vect-add-mic
+
+### Execution of the Program in Native Mode on Intel Xeon Phi
+
+The user access to the Intel Xeon Phi is through the SSH. Since user
+home directories are mounted using NFS on the accelerator, users do not
+have to copy binary files or libraries between the host and accelerator.
+Â
+
+Get the PATH of MIC enabled libraries for currently used Intel Compiler
+(here was icc/2015.3.187-GNU-5.1.0-2.25 used) :
+
+ $ echo $MIC_LD_LIBRARY_PATH
+ /apps/all/icc/2015.3.187-GNU-5.1.0-2.25/composer_xe_2015.3.187/compiler/lib/mic
+
+To connect to the accelerator run:
+
+ $ ssh mic0
+
+If the code is sequential, it can be executed directly:
+
+ mic0 $ ~/path_to_binary/vect-add-seq-mic
+
+If the code is parallelized using OpenMP a set of additional libraries
+is required for execution. To locate these libraries new path has to be
+added to the LD_LIBRARY_PATH environment variable prior to the
+execution:
+
+ mic0 $ export LD_LIBRARY_PATH=/apps/all/icc/2015.3.187-GNU-5.1.0-2.25/composer_xe_2015.3.187/compiler/lib/mic:$LD_LIBRARY_PATH
+
+Please note that the path exported in the previous example contains path
+to a specific compiler (here the version is 2015.3.187-GNU-5.1.0-2.25).
+This version number has to match with the version number of the Intel
+compiler module that was used to compile the code on the host computer.
+
+For your information the list of libraries and their location required
+for execution of an OpenMP parallel code on Intel Xeon Phi is:
+
+/apps/all/icc/2015.3.187-GNU-5.1.0-2.25/composer_xe_2015.3.187/compiler/lib/mic
+
+libiomp5.so
+libimf.so
+libsvml.so
+libirng.so
+libintlc.so.5
+
+Finally, to run the compiled code use:
+
+ $ ~/path_to_binary/vect-add-mic
+
+OpenCL
+-------------------
+
+OpenCL (Open Computing Language) is an open standard for
+general-purpose parallel programming for diverse mix of multi-core CPUs,
+GPU coprocessors, and other parallel processors. OpenCL provides a
+flexible execution model and uniform programming environment for
+software developers to write portable code for systems running on both
+the CPU and graphics processors or accelerators like the Intel® Xeon
+Phi.
+
+On Anselm OpenCL is installed only on compute nodes with MIC
+accelerator, therefore OpenCL code can be compiled only on these nodes.
+
+ module load opencl-sdk opencl-rt
+
+Always load "opencl-sdk" (providing devel files like headers) and
+"opencl-rt" (providing dynamic library libOpenCL.so) modules to compile
+and link OpenCL code. Load "opencl-rt" for running your compiled code.
+
+There are two basic examples of OpenCL code in the following
+directory:
+
+ /apps/intel/opencl-examples/
+
+First example "CapsBasic" detects OpenCL compatible hardware, here
+CPU and MIC, and prints basic information about the capabilities of
+it.Â
+
+ /apps/intel/opencl-examples/CapsBasic/capsbasic
+
+To compile and run the example copy it to your home directory, get
+a PBS interactive session on of the nodes with MIC and run make for
+compilation. Make files are very basic and shows how the OpenCL code can
+be compiled on Anselm.
+
+ $ cp /apps/intel/opencl-examples/CapsBasic/* .
+ $ qsub -I -q qprod -l select=1:ncpus=24:accelerator=True:naccelerators=2:accelerator_model=phi7120 -A NONE-0-0
+ $ make
+
+The compilation command for this example is:
+
+ $ g++ capsbasic.cpp -lOpenCL -o capsbasic -I/apps/intel/opencl/include/
+
+After executing the complied binary file, following output should
+be displayed.
+
+ ./capsbasic
+
+ Number of available platforms: 1
+ Platform names:
+ Â Â Â [0] Intel(R) OpenCL [Selected]
+ Number of devices available for each type:
+ Â Â Â CL_DEVICE_TYPE_CPU: 1
+ Â Â Â CL_DEVICE_TYPE_GPU: 0
+ Â Â Â CL_DEVICE_TYPE_ACCELERATOR: 1
+
+ ** Detailed information for each device ***
+
+ CL_DEVICE_TYPE_CPU[0]
+ Â Â Â CL_DEVICE_NAME:Â Â Â Â Â Â Â Intel(R) Xeon(R) CPU E5-2470 0 @ 2.30GHz
+ Â Â Â CL_DEVICE_AVAILABLE: 1
+
+ ...
+
+ CL_DEVICE_TYPE_ACCELERATOR[0]
+ Â Â Â CL_DEVICE_NAME: Intel(R) Many Integrated Core Acceleration Card
+ Â Â Â CL_DEVICE_AVAILABLE: 1
+
+ ...
+
+More information about this example can be found on Intel website:
+<http://software.intel.com/en-us/vcsource/samples/caps-basic/>
+
+The second example that can be found in
+"/apps/intel/opencl-examples" >directory is General Matrix
+Multiply. You can follow the the same procedure to download the example
+to your directory and compile it.Â
+
+ $ cp -r /apps/intel/opencl-examples/* .
+ $ qsub -I -q qprod -l select=1:ncpus=24:accelerator=True:naccelerators=2:accelerator_model=phi7120 -A NONE-0-0
+ $ cd GEMM
+ $ make
+
+The compilation command for this example is:
+
+ $ g++ cmdoptions.cpp gemm.cpp ../common/basic.cpp ../common/cmdparser.cpp ../common/oclobject.cpp -I../common -lOpenCL -o gemm -I/apps/intel/opencl/include/
+
+To see the performance of Intel Xeon Phi performing the DGEMM run
+the example as follows:
+
+ ./gemm -d 1
+ Platforms (1):
+ [0] Intel(R) OpenCL [Selected]
+ Devices (2):
+ [0] Intel(R) Xeon(R) CPU E5-2470 0 @ 2.30GHz
+ [1] Intel(R) Many Integrated Core Acceleration Card [Selected]
+ Build program options: "-DT=float -DTILE_SIZE_M=1 -DTILE_GROUP_M=16 -DTILE_SIZE_N=128 -DTILE_GROUP_N=1 -DTILE_SIZE_K=8"
+ Running gemm_nn kernel with matrix size: 3968x3968
+ Memory row stride to ensure necessary alignment: 15872 bytes
+ Size of memory region for one matrix: 62980096 bytes
+ Using alpha = 0.57599 and beta = 0.872412
+ ...
+ Host time: 0.292953 sec.
+ Host perf: 426.635 GFLOPS
+ Host time: 0.293334 sec.
+ Host perf: 426.081 GFLOPS
+ ...
+
+Please note: GNU compiler is used to compile the OpenCL codes for
+Intel MIC. You do not need to load Intel compiler module.
+
+MPI
+----------------
+
+### Environment setup and compilation
+
+To achieve best MPI performance always use following setup for Intel MPI
+on Xeon Phi accelerated nodes:
+
+ $ export I_MPI_FABRICS=shm:dapl
+ $ export I_MPI_DAPL_PROVIDER_LIST=ofa-v2-mlx4_0-1u,ofa-v2-scif0,ofa-v2-mcm-1
+
+This ensures, that MPI inside node will use SHMEM communication, between
+HOST and Phi the IB SCIF will be used and between different nodes or
+Phi's on diferent nodes a CCL-Direct proxy will be used.
+
+Please note: Other FABRICS like tcp,ofa may be used (even combined with
+shm) but there's severe loss of performance (by order of magnitude).
+Usage of single DAPL PROVIDER (e. g.
+I_MPI_DAPL_PROVIDER=ofa-v2-mlx4_0-1u) will cause failure of
+Host<->Phi and/or Phi<->Phi communication.
+Usage of the I_MPI_DAPL_PROVIDER_LIST on non-accelerated node will
+cause failure of any MPI communication, since those nodes don't have
+SCIF device and there's no CCL-Direct proxy runnig.
+
+Again an MPI code for Intel Xeon Phi has to be compiled on a compute
+node with accelerator and MPSS software stack installed. To get to a
+compute node with accelerator use:
+
+ $ qsub -I -q qprod -l select=1:ncpus=24:accelerator=True:naccelerators=2:accelerator_model=phi7120 -A NONE-0-0
+
+The only supported implementation of MPI standard for Intel Xeon Phi is
+Intel MPI. To setup a fully functional development environment a
+combination of Intel compiler and Intel MPI has to be used. On a host
+load following modules before compilation:
+
+ $ module load intel impi
+
+To compile an MPI code for host use:
+
+ $ mpiicc -xhost -o mpi-test mpi-test.c
+
+To compile the same code for Intel Xeon Phi architecture use:
+
+ $ mpiicc -mmic -o mpi-test-mic mpi-test.c
+
+Or, if you are using Fortran :
+
+ $ mpiifort -mmic -o mpi-test-mic mpi-test.f90
+
+An example of basic MPI version of "hello-world" example in C language,
+that can be executed on both host and Xeon Phi is (can be directly copy
+and pasted to a .c file)
+
+`
+#include <stdio.h>
+#include <mpi.h>
+
+int main (argc, argv)
+Â Â Â Â int argc;
+Â Â Â Â char *argv[];
+{
+Â int rank, size;
+
+Â int len;
+Â char node[MPI_MAX_PROCESSOR_NAME];
+
+Â MPI_Init (&argc, &argv);Â Â Â Â Â /* starts MPI */
+Â MPI_Comm_rank (MPI_COMM_WORLD, &rank);Â Â Â Â Â Â Â /* get current process id */
+Â MPI_Comm_size (MPI_COMM_WORLD, &size);Â Â Â Â Â Â Â /* get number of processes */
+
+Â MPI_Get_processor_name(node,&len);
+
+Â printf( "Hello world from process %d of %d on host %s n", rank, size, node );
+Â MPI_Finalize();
+Â return 0;
+}
+`
+
+### MPI programming models
+
+Intel MPI for the Xeon Phi coprocessors offers different MPI
+programming models:
+
+Host-only model** - all MPI ranks reside on the host. The coprocessors
+can be used by using offload pragmas. (Using MPI calls inside offloaded
+code is not supported.)**
+
+Coprocessor-only model** - all MPI ranks reside only on the
+coprocessors.
+
+Symmetric model** - the MPI ranks reside on both the host and the
+coprocessor. Most general MPI case.
+
+###Host-only model
+
+In this case all environment variables are set by modules,
+so to execute the compiled MPI program on a single node, use:
+
+ $ mpirun -np 4 ./mpi-test
+
+The output should be similar to:
+
+ Hello world from process 1 of 4 on host r38u31n1000
+ Hello world from process 3 of 4 on host r38u31n1000
+ Hello world from process 2 of 4 on host r38u31n1000
+ Hello world from process 0 of 4 on host r38u31n1000
+
+### Coprocessor-only model
+
+There are two ways how to execute an MPI code on a single
+coprocessor: 1.) lunch the program using "**mpirun**" from the
+coprocessor; or 2.) lunch the task using "**mpiexec.hydra**" from a
+host.
+
+Execution on coprocessor**Â
+
+Similarly to execution of OpenMP programs in native mode, since the
+environmental module are not supported on MIC, user has to setup paths
+to Intel MPI libraries and binaries manually. One time setup can be done
+by creating a "**.profile**" file in user's home directory. This file
+sets up the environment on the MIC automatically once user access to the
+accelerator through the SSH.
+
+At first get the LD_LIBRARY_PATH for currenty used Intel Compiler and
+Intel MPI:
+
+ $ echo $MIC_LD_LIBRARY_PATH
+ /apps/all/imkl/11.2.3.187-iimpi-7.3.5-GNU-5.1.0-2.25/mkl/lib/mic:/apps/all/imkl/11.2.3.187-iimpi-7.3.5-GNU-5.1.0-2.25/lib/mic:/apps/all/icc/2015.3.187-GNU-5.1.0-2.25/composer_xe_2015.3.187/compiler/lib/mic/
+
+Use it in your ~/.profile:
+
+ $ vim ~/.profile
+
+ PS1='[u@h W]$ '
+ export PATH=/usr/bin:/usr/sbin:/bin:/sbin
+
+ #IMPI
+ export PATH=/apps/all/impi/5.0.3.048-iccifort-2015.3.187-GNU-5.1.0-2.25/mic/bin/:$PATH
+
+ #OpenMP (ICC, IFORT), IMKL and IMPI
+ export LD_LIBRARY_PATH=/apps/all/imkl/11.2.3.187-iimpi-7.3.5-GNU-5.1.0-2.25/mkl/lib/mic:/apps/all/imkl/11.2.3.187-iimpi-7.3.5-GNU-5.1.0-2.25/lib/mic:/apps/all/icc/2015.3.187-GNU-5.1.0-2.25/composer_xe_2015.3.187/compiler/lib/mic:$LD_LIBRARY_PATH
+
+Please note:
+Â - this file sets up both environmental variable for both MPI and OpenMP
+libraries.
+Â - this file sets up the paths to a particular version of Intel MPI
+library and particular version of an Intel compiler. These versions have
+to match with loaded modules.
+
+To access a MIC accelerator located on a node that user is currently
+connected to, use:
+
+ $ ssh mic0
+
+or in case you need specify a MIC accelerator on a particular node, use:
+
+ $ ssh r38u31n1000-mic0
+
+To run the MPI code in parallel on multiple core of the accelerator,
+use:
+
+ $ mpirun -np 4 ./mpi-test-mic
+
+The output should be similar to:
+
+ Hello world from process 1 of 4 on host r38u31n1000-mic0
+ Hello world from process 2 of 4 on host r38u31n1000-mic0
+ Hello world from process 3 of 4 on host r38u31n1000-mic0
+ Hello world from process 0 of 4 on host r38u31n1000-mic0
+
+Â **
+
+**Execution on host**
+
+If the MPI program is launched from host instead of the coprocessor, the
+environmental variables are not set using the ".profile" file. Therefore
+user has to specify library paths from the command line when calling
+"mpiexec".
+
+First step is to tell mpiexec that the MPI should be executed on a local
+accelerator by setting up the environmental variable "I_MPI_MIC"
+
+ $ export I_MPI_MIC=1
+
+Now the MPI program can be executed as:
+
+ $ mpirun -genv LD_LIBRARY_PATH $MIC_LD_LIBRARY_PATH -host mic0 -n 4 ~/mpi-test-mic
+
+or using mpirun
+
+ $ mpirun -genv LD_LIBRARY_PATH $MIC_LD_LIBRARY_PATH -host mic0 -n 4 ~/mpi-test-mic
+
+Please note:
+Â - the full path to the binary has to specified (here:
+"**>~/mpi-test-mic**")
+Â - the LD_LIBRARY_PATH has to match with Intel MPI module used to
+compile the MPI code
+
+The output should be again similar to:
+
+ Hello world from process 1 of 4 on host r38u31n1000-mic0
+ Hello world from process 2 of 4 on host r38u31n1000-mic0
+ Hello world from process 3 of 4 on host r38u31n1000-mic0
+ Hello world from process 0 of 4 on host r38u31n1000-mic0
+
+Please note that the "mpiexec.hydra" requires a file
+"**>pmi_proxy**" from Intel MPI library to be copied to the
+MIC filesystem. If the file is missing please contact the system
+administrators. A simple test to see if the file is present is to
+execute:
+
+ Â Â $ ssh mic0 ls /bin/pmi_proxy
+ Â /bin/pmi_proxy
+
+Â **
+
+**Execution on host - MPI processes distributed over multiple
+accelerators on multiple nodes**
+
+To get access to multiple nodes with MIC accelerator, user has to
+use PBS to allocate the resources. To start interactive session, that
+allocates 2 compute nodes = 2 MIC accelerators run qsub command with
+following parameters:
+
+ $ qsub -I -q qprod -l select=2:ncpus=24:accelerator=True:naccelerators=2:accelerator_model=phi7120 -A NONE-0-0
+
+ $ module load intel impi
+
+This command connects user through ssh to one of the nodes
+immediately. To see the other nodes that have been allocated use:
+
+ $ cat $PBS_NODEFILE
+
+For example:
+
+ r38u31n1000.bullx
+ r38u32n1001.bullx
+
+This output means that the PBS allocated nodes r38u31n1000 and
+r38u32n1001, which means that user has direct access to
+"**r38u31n1000-mic0**" and "**>r38u32n1001-mic0**"
+accelerators.
+
+Please note: At this point user can connect to any of the
+allocated nodes or any of the allocated MIC accelerators using ssh:
+- to connect to the second node : ** $
+ssh >r38u32n1001**
+- to connect to the accelerator on the first node from the first
+node: **$ ssh
+r38u31n1000-mic0** or **
+$ ssh mic0**
+-** to connect to the accelerator on the second node from the first
+node: **$ ssh
+r38u32n1001-mic0**
+
+At this point we expect that correct modules are loaded and binary
+is compiled. For parallel execution the mpiexec.hydra is used.
+Again the first step is to tell mpiexec that the MPI can be executed on
+MIC accelerators by setting up the environmental variable "I_MPI_MIC",
+don't forget to have correct FABRIC and PROVIDER defined.
+
+ $ export I_MPI_MIC=1
+ $ export I_MPI_FABRICS=shm:dapl
+ $ export I_MPI_DAPL_PROVIDER_LIST=ofa-v2-mlx4_0-1u,ofa-v2-scif0,ofa-v2-mcm-1
+
+The launch the MPI program use:
+
+ $ mpirun -genv LD_LIBRARY_PATH $MIC_LD_LIBRARY_PATH
+ -host r38u31n1000-mic0 -n 4 ~/mpi-test-mic
+ : -host r38u32n1001-mic0 -n 6 ~/mpi-test-mic
+
+or using mpirun:
+
+ $ mpirun -genv LD_LIBRARY_PATH
+ -host r38u31n1000-mic0 -n 4 ~/mpi-test-mic
+ : -host r38u32n1001-mic0 -n 6 ~/mpi-test-mic
+
+In this case four MPI processes are executed on accelerator
+r38u31n1000-mic and six processes are executed on accelerator
+r38u32n1001-mic0. The sample output (sorted after execution) is:
+
+ Hello world from process 0 of 10 on host r38u31n1000-mic0
+ Hello world from process 1 of 10 on host r38u31n1000-mic0
+ Hello world from process 2 of 10 on host r38u31n1000-mic0
+ Hello world from process 3 of 10 on host r38u31n1000-mic0
+ Hello world from process 4 of 10 on host r38u32n1001-mic0
+ Hello world from process 5 of 10 on host r38u32n1001-mic0
+ Hello world from process 6 of 10 on host r38u32n1001-mic0
+ Hello world from process 7 of 10 on host r38u32n1001-mic0
+ Hello world from process 8 of 10 on host r38u32n1001-mic0
+ Hello world from process 9 of 10 on host r38u32n1001-mic0
+
+The same way MPI program can be executed on multiple hosts:Â
+
+ $ mpirun -genv LD_LIBRARY_PATH $MIC_LD_LIBRARY_PATH
+ -host r38u31n1000 -n 4 ~/mpi-test
+ : -host r38u32n1001 -n 6 ~/mpi-test
+
+###Symmetric model
+
+In a symmetric mode MPI programs are executed on both host
+computer(s) and MIC accelerator(s). Since MIC has a different
+architecture and requires different binary file produced by the Intel
+compiler two different files has to be compiled before MPI program is
+executed.
+
+In the previous section we have compiled two binary files, one for
+hosts "**mpi-test**" and one for MIC accelerators "**mpi-test-mic**".
+These two binaries can be executed at once using mpiexec.hydra:
+
+ $ mpirun
+ -genv $MIC_LD_LIBRARY_PATH
+ -host r38u32n1001 -n 2 ~/mpi-test
+ : -host r38u32n1001-mic0 -n 2 ~/mpi-test-mic
+
+In this example the first two parameters (line 2 and 3) sets up required
+environment variables for execution. The third line specifies binary
+that is executed on host (here r38u32n1001) and the last line specifies
+the binary that is execute on the accelerator (here r38u32n1001-mic0).
+
+The output of the program is:
+
+ Hello world from process 0 of 4 on host r38u32n1001
+ Hello world from process 1 of 4 on host r38u32n1001
+ Hello world from process 2 of 4 on host r38u32n1001-mic0
+ Hello world from process 3 of 4 on host r38u32n1001-mic0
+
+The execution procedure can be simplified by using the mpirun
+command with the machine file a a parameter. Machine file contains list
+of all nodes and accelerators that should used to execute MPI processes.
+
+An example of a machine file that uses 2 >hosts (r38u32n1001
+and r38u33n1002) and 2 accelerators **(r38u32n1001-mic0** and
+r38u33n1002-mic0**) to run 2 MPI processes
+on each of them:
+
+ $ cat hosts_file_mix
+ r38u32n1001:2
+ r38u32n1001-mic0:2
+ r38u33n1002:2
+ r38u33n1002-mic0:2
+
+In addition if a naming convention is set in a way that the name
+of the binary for host is **"bin_name"**Â and the name of the binary
+for the accelerator is **"bin_name-mic"** then by setting up the
+environment variable **I_MPI_MIC_POSTFIX** to **"-mic"** user do not
+have to specify the names of booth binaries. In this case mpirun needs
+just the name of the host binary file (i.e. "mpi-test") and uses the
+suffix to get a name of the binary for accelerator (i..e.
+"mpi-test-mic").
+
+ $ export I_MPI_MIC_POSTFIX=-mic
+
+Â >To run the MPI code using mpirun and the machine file
+"hosts_file_mix" use:
+
+ $ mpirun
+ -genv LD_LIBRARY_PATH $MIC_LD_LIBRARY_PATH
+ -machinefile hosts_file_mix
+ ~/mpi-test
+
+A possible output of the MPI "hello-world" example executed on two
+hosts and two accelerators is:
+
+ Hello world from process 0 of 8 on host r38u31n1000
+ Hello world from process 1 of 8 on host r38u31n1000
+ Hello world from process 2 of 8 on host r38u31n1000-mic0
+ Hello world from process 3 of 8 on host r38u31n1000-mic0
+ Hello world from process 4 of 8 on host r38u32n1001
+ Hello world from process 5 of 8 on host r38u32n1001
+ Hello world from process 6 of 8 on host r38u32n1001-mic0
+ Hello world from process 7 of 8 on host r38u32n1001-mic0
+
+Using the PBS automatically generated node-files
+
+PBS also generates a set of node-files that can be used instead of
+manually creating a new one every time. Three node-files are genereated:
+
+**Host only node-file:**
+Â - /lscratch/${PBS_JOBID}/nodefile-cn
+MIC only node-file:
+Â - /lscratch/${PBS_JOBID}/nodefile-mic
+Host and MIC node-file:
+Â - /lscratch/${PBS_JOBID}/nodefile-mix
+
+Please note each host or accelerator is listed only per files. User has
+to specify how many jobs should be executed per node using "-n"
+parameter of the mpirun command.
+
+Optimization
+------------
+
+For more details about optimization techniques please read Intel
+document [Optimization and Performance Tuning for Intel® Xeon Phi™
+Coprocessors](http://software.intel.com/en-us/articles/optimization-and-performance-tuning-for-intel-xeon-phi-coprocessors-part-1-optimization "http://software.intel.com/en-us/articles/optimization-and-performance-tuning-for-intel-xeon-phi-coprocessors-part-1-optimization")
+
diff --git a/converted/docs.it4i.cz/salomon/software/java.md b/converted/docs.it4i.cz/salomon/software/java.md
new file mode 100644
index 0000000000000000000000000000000000000000..ced88c9ef38aacf8874e167640e971e2ace9274b
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/java.md
@@ -0,0 +1,33 @@
+Java
+====
+
+Java on the cluster
+
+
+
+Java is available on the cluster. Activate java by loading the Java
+module
+
+ $ module load Java
+
+Note that the Java module must be loaded on the compute nodes as well,
+in order to run java on compute nodes.
+
+Check for java version and path
+
+ $ java -version
+ $ which java
+
+With the module loaded, not only the runtime environment (JRE), but also
+the development environment (JDK) with the compiler is available.
+
+ $ javac -version
+ $ which javac
+
+Java applications may use MPI for interprocess communication, in
+conjunction with OpenMPI. Read more
+on <http://www.open-mpi.org/faq/?category=java>.
+This functionality is currently not supported on Anselm cluster. In case
+you require the java interface to MPI, please contact [cluster
+support](https://support.it4i.cz/rt/).
+
diff --git a/converted/docs.it4i.cz/salomon/software/mpi-1/Running_OpenMPI.md b/converted/docs.it4i.cz/salomon/software/mpi-1/Running_OpenMPI.md
new file mode 100644
index 0000000000000000000000000000000000000000..856a3e95e6d41dbbe6eb756762fa53fa50ed2164
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/mpi-1/Running_OpenMPI.md
@@ -0,0 +1,241 @@
+Running OpenMPI
+===============
+
+
+
+OpenMPI program execution
+-------------------------
+
+The OpenMPI programs may be executed only via the PBS Workload manager,
+by entering an appropriate queue. On the cluster, the **OpenMPI 1.8.6**
+is OpenMPI based MPI implementation.
+
+### Basic usage
+
+Use the mpiexec to run the OpenMPI code.
+
+Example:
+
+ $ qsub -q qexp -l select=4:ncpus=24 -I
+ qsub: waiting for job 15210.isrv5 to start
+ qsub: job 15210.isrv5 ready
+
+ $ pwd
+ /home/username
+
+ $ module load OpenMPI
+ $ mpiexec -pernode ./helloworld_mpi.x
+ Hello world! from rank 0 of 4 on host r1i0n17
+ Hello world! from rank 1 of 4 on host r1i0n5
+ Hello world! from rank 2 of 4 on host r1i0n6
+ Hello world! from rank 3 of 4 on host r1i0n7
+
+Please be aware, that in this example, the directive **-pernode** is
+used to run only **one task per node**, which is normally an unwanted
+behaviour (unless you want to run hybrid code with just one MPI and 24
+OpenMP tasks per node). In normal MPI programs **omit the -pernode
+directive** to run up to 24 MPI tasks per each node.
+
+In this example, we allocate 4 nodes via the express queue
+interactively. We set up the openmpi environment and interactively run
+the helloworld_mpi.x program.
+Note that the executable
+helloworld_mpi.x must be available within the
+same path on all nodes. This is automatically fulfilled on the /home and
+/scratch filesystem.
+
+You need to preload the executable, if running on the local ramdisk /tmp
+filesystem
+
+ $ pwd
+ /tmp/pbs.15210.isrv5
+
+ $ mpiexec -pernode --preload-binary ./helloworld_mpi.x
+ Hello world! from rank 0 of 4 on host r1i0n17
+ Hello world! from rank 1 of 4 on host r1i0n5
+ Hello world! from rank 2 of 4 on host r1i0n6
+ Hello world! from rank 3 of 4 on host r1i0n7
+
+In this example, we assume the executable
+helloworld_mpi.x is present on compute node
+r1i0n17 on ramdisk. We call the mpiexec whith the **--preload-binary**
+argument (valid for openmpi). The mpiexec will copy the executable from
+r1i0n17 to the /tmp/pbs.15210.isrv5
+directory on r1i0n5, r1i0n6 and r1i0n7 and execute the program.
+
+MPI process mapping may be controlled by PBS parameters.
+
+The mpiprocs and ompthreads parameters allow for selection of number of
+running MPI processes per node as well as number of OpenMP threads per
+MPI process.
+
+### One MPI process per node
+
+Follow this example to run one MPI process per node, 24 threads per
+process.Â
+
+ $ qsub -q qexp -l select=4:ncpus=24:mpiprocs=1:ompthreads=24 -I
+
+ $ module load OpenMPI
+
+ $ mpiexec --bind-to-none ./helloworld_mpi.x
+
+In this example, we demonstrate recommended way to run an MPI
+application, using 1 MPI processes per node and 24 threads per socket,
+on 4 nodes.
+
+### Two MPI processes per node
+
+Follow this example to run two MPI processes per node, 8 threads per
+process. Note the options to mpiexec.
+
+ $ qsub -q qexp -l select=4:ncpus=24:mpiprocs=2:ompthreads=12 -I
+
+ $ module load OpenMPI
+
+ $ mpiexec -bysocket -bind-to-socket ./helloworld_mpi.x
+
+In this example, we demonstrate recommended way to run an MPI
+application, using 2 MPI processes per node and 12 threads per socket,
+each process and its threads bound to a separate processor socket of the
+node, on 4 nodes
+
+### 24 MPI processes per node
+
+Follow this example to run 24 MPI processes per node, 1 thread per
+process. Note the options to mpiexec.
+
+ $ qsub -q qexp -l select=4:ncpus=24:mpiprocs=24:ompthreads=1 -I
+
+ $ module load OpenMPI
+
+ $ mpiexec -bycore -bind-to-core ./helloworld_mpi.x
+
+In this example, we demonstrate recommended way to run an MPI
+application, using 24 MPI processes per node, single threaded. Each
+process is bound to separate processor core, on 4 nodes.
+
+### OpenMP thread affinity
+
+Important! Bind every OpenMP thread to a core!
+
+In the previous two examples with one or two MPI processes per node, the
+operating system might still migrate OpenMP threads between cores. You
+might want to avoid this by setting these environment variable for GCC
+OpenMP:
+
+ $ export GOMP_CPU_AFFINITY="0-23"
+
+or this one for Intel OpenMP:
+
+ $ export KMP_AFFINITY=granularity=fine,compact,1,0
+
+As of OpenMP 4.0 (supported by GCC 4.9 and later and Intel 14.0 and
+later) the following variables may be used for Intel or GCC:
+
+ $ export OMP_PROC_BIND=true
+ $ export OMP_PLACES=coresÂ
+
+OpenMPI Process Mapping and Binding
+------------------------------------------------
+
+The mpiexec allows for precise selection of how the MPI processes will
+be mapped to the computational nodes and how these processes will bind
+to particular processor sockets and cores.
+
+MPI process mapping may be specified by a hostfile or rankfile input to
+the mpiexec program. Altough all implementations of MPI provide means
+for process mapping and binding, following examples are valid for the
+openmpi only.
+
+### Hostfile
+
+Example hostfile
+
+ r1i0n17.smc.salomon.it4i.cz
+ r1i0n5.smc.salomon.it4i.cz
+ r1i0n6.smc.salomon.it4i.cz
+ r1i0n7.smc.salomon.it4i.cz
+
+Use the hostfile to control process placement
+
+ $ mpiexec -hostfile hostfile ./helloworld_mpi.x
+ Hello world! from rank 0 of 4 on host r1i0n17
+ Hello world! from rank 1 of 4 on host r1i0n5
+ Hello world! from rank 2 of 4 on host r1i0n6
+ Hello world! from rank 3 of 4 on host r1i0n7
+
+In this example, we see that ranks have been mapped on nodes according
+to the order in which nodes show in the hostfile
+
+### Rankfile
+
+Exact control of MPI process placement and resource binding is provided
+by specifying a rankfile
+
+Appropriate binding may boost performance of your application.
+
+Example rankfile
+
+ rank 0=r1i0n7.smc.salomon.it4i.cz slot=1:0,1
+ rank 1=r1i0n6.smc.salomon.it4i.cz slot=0:*
+ rank 2=r1i0n5.smc.salomon.it4i.cz slot=1:1-2
+ rank 3=r1i0n17.smc.salomon slot=0:1,1:0-2
+ rank 4=r1i0n6.smc.salomon.it4i.cz slot=0:*,1:*
+
+This rankfile assumes 5 ranks will be running on 4 nodes and provides
+exact mapping and binding of the processes to the processor sockets and
+cores
+
+Explanation:
+rank 0 will be bounded to r1i0n7, socket1 core0 and core1
+rank 1 will be bounded to r1i0n6, socket0, all cores
+rank 2 will be bounded to r1i0n5, socket1, core1 and core2
+rank 3 will be bounded to r1i0n17, socket0 core1, socket1 core0, core1,
+core2
+rank 4 will be bounded to r1i0n6, all cores on both sockets
+
+ $ mpiexec -n 5 -rf rankfile --report-bindings ./helloworld_mpi.x
+ [r1i0n17:11180] MCW rank 3 bound to socket 0[core 1] socket 1[core 0-2]: [. B . . . . . . . . . .][B B B . . . . . . . . .] (slot list 0:1,1:0-2)
+ [r1i0n7:09928] MCW rank 0 bound to socket 1[core 0-1]: [. . . . . . . . . . . .][B B . . . . . . . . . .] (slot list 1:0,1)
+ [r1i0n6:10395] MCW rank 1 bound to socket 0[core 0-7]: [B B B B B B B B B B B B][. . . . . . . . . . . .] (slot list 0:*)
+ [r1i0n5:10406] MCW rank 2 bound to socket 1[core 1-2]: [. . . . . . . . . . . .][. B B . . . . . . . . .] (slot list 1:1-2)
+ [r1i0n6:10406] MCW rank 4 bound to socket 0[core 0-7] socket 1[core 0-7]: [B B B B B B B B B B B B][B B B B B B B B B B B B] (slot list 0:*,1:*)
+ Hello world! from rank 3 of 5 on host r1i0n17
+ Hello world! from rank 1 of 5 on host r1i0n6
+ Hello world! from rank 0 of 5 on host r1i0n7
+ Hello world! from rank 4 of 5 on host r1i0n6
+ Hello world! from rank 2 of 5 on host r1i0n5
+
+In this example we run 5 MPI processes (5 ranks) on four nodes. The
+rankfile defines how the processes will be mapped on the nodes, sockets
+and cores. The **--report-bindings** option was used to print out the
+actual process location and bindings. Note that ranks 1 and 4 run on the
+same node and their core binding overlaps.
+
+It is users responsibility to provide correct number of ranks, sockets
+and cores.
+
+### Bindings verification
+
+In all cases, binding and threading may be verified by executing for
+example:
+
+ $ mpiexec -bysocket -bind-to-socket --report-bindings echo
+ $ mpiexec -bysocket -bind-to-socket numactl --show
+ $ mpiexec -bysocket -bind-to-socket echo $OMP_NUM_THREADS
+
+Changes in OpenMPI 1.8
+----------------------
+
+Some options have changed in OpenMPI version 1.8.
+
+ |version 1.6.5 |version 1.8.1 |
+ | --- | --- |
+ |--bind-to-none |--bind-to none |
+ |--bind-to-core |--bind-to core |
+ |--bind-to-socket |--bind-to socket |
+ |-bysocket |--map-by socket |
+ |-bycore |--map-by core |
+ |-pernode |--map-by ppr:1:node\ |
+
diff --git a/converted/docs.it4i.cz/salomon/software/mpi-1/mpi.md b/converted/docs.it4i.cz/salomon/software/mpi-1/mpi.md
new file mode 100644
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@@ -0,0 +1,185 @@
+MPI
+===
+
+
+
+Setting up MPI Environment
+--------------------------
+
+The Salomon cluster provides several implementations of the MPI library:
+
+ -------------------------------------------------------------------------
+ MPI Library Thread support
+ ------ |---|---|---
+ **Intel MPI 4.1** Full thread support up to
+ MPI_THREAD_MULTIPLE
+
+ **Intel MPI 5.0** Full thread support up to
+ MPI_THREAD_MULTIPLE
+
+ OpenMPI 1.8.6 Full thread support up to
+ MPI_THREAD_MULTIPLE, MPI-3.0
+ support
+
+ SGI MPT 2.12
+ -------------------------------------------------------------------------
+
+MPI libraries are activated via the environment modules.
+
+Look up section modulefiles/mpi in module avail
+
+ $ module avail
+ ------------------------------ /apps/modules/mpi -------------------------------
+ impi/4.1.1.036-iccifort-2013.5.192
+ impi/4.1.1.036-iccifort-2013.5.192-GCC-4.8.3
+ impi/5.0.3.048-iccifort-2015.3.187
+ impi/5.0.3.048-iccifort-2015.3.187-GNU-5.1.0-2.25
+ MPT/2.12
+ OpenMPI/1.8.6-GNU-5.1.0-2.25
+
+There are default compilers associated with any particular MPI
+implementation. The defaults may be changed, the MPI libraries may be
+used in conjunction with any compiler.
+The defaults are selected via the modules in following way
+
+ --------------------------------------------------------------------------
+ Module MPI Compiler suite
+ ------------------ |---|---|-------------- ------------------------
+ impi-5.0.3.048-iccifort- Intel MPI 5.0.3
+ 2015.3.187
+
+ OpenMP-1.8.6-GNU-5.1.0-2 OpenMPI 1.8.6
+ .25
+ --------------------------------------------------------------------------
+
+Examples:
+
+ $ module load gompi/2015b
+
+In this example, we activate the latest OpenMPI with latest GNU
+compilers (OpenMPI 1.8.6 and GCC 5.1). Please see more information about
+toolchains in section [Environment and
+Modules](../../environment-and-modules.html)Â .
+
+To use OpenMPI with the intel compiler suite, use
+
+ $ module load iompi/2015.03
+
+In this example, the openmpi 1.8.6 using intel compilers is activated.
+It's used "iompi" toolchain.
+
+Compiling MPI Programs
+----------------------
+
+After setting up your MPI environment, compile your program using one of
+the mpi wrappers
+
+ $ mpicc -v
+ $ mpif77 -v
+ $ mpif90 -v
+
+When using Intel MPI, use the following MPI wrappers:
+
+ $ mpicc
+ $ mpiifortÂ
+
+Wrappers mpif90, mpif77 that are provided by Intel MPI are designed for
+gcc and gfortran. You might be able to compile MPI code by them even
+with Intel compilers, but you might run into problems (for example,
+native MIC compilation with -mmic does not work with mpif90).
+
+Example program:
+
+ // helloworld_mpi.c
+ #include <stdio.h>
+
+ #include<mpi.h>
+
+ int main(int argc, char **argv) {
+
+ int len;
+ int rank, size;
+ char node[MPI_MAX_PROCESSOR_NAME];
+
+ // Initiate MPI
+ MPI_Init(&argc, &argv);
+ MPI_Comm_rank(MPI_COMM_WORLD,&rank);
+ MPI_Comm_size(MPI_COMM_WORLD,&size);
+
+ // Get hostame and print
+ MPI_Get_processor_name(node,&len);
+ printf("Hello world! from rank %d of %d on host %sn",rank,size,node);
+
+ // Finalize and exit
+ MPI_Finalize();
+
+ return 0;
+ }
+
+Compile the above example with
+
+ $ mpicc helloworld_mpi.c -o helloworld_mpi.x
+
+Running MPI Programs
+--------------------
+
+The MPI program executable must be compatible with the loaded MPI
+module.
+Always compile and execute using the very same MPI module.
+
+It is strongly discouraged to mix mpi implementations. Linking an
+application with one MPI implementation and running mpirun/mpiexec form
+other implementation may result in unexpected errors.
+
+The MPI program executable must be available within the same path on all
+nodes. This is automatically fulfilled on the /home and /scratch
+filesystem. You need to preload the executable, if running on the local
+scratch /lscratch filesystem.
+
+### Ways to run MPI programs
+
+Optimal way to run an MPI program depends on its memory requirements,
+memory access pattern and communication pattern.
+
+Consider these ways to run an MPI program:
+1. One MPI process per node, 24 threads per process
+2. Two MPI processes per node, 12 threads per process
+3. 24 MPI processes per node, 1 thread per process.
+
+One MPI** process per node, using 24 threads, is most useful for
+memory demanding applications, that make good use of processor cache
+memory and are not memory bound. This is also a preferred way for
+communication intensive applications as one process per node enjoys full
+bandwidth access to the network interface.Â
+
+Two MPI** processes per node, using 12 threads each, bound to
+processor socket is most useful for memory bandwidth bound applications
+such as BLAS1 or FFT, with scalable memory demand. However, note that
+the two processes will share access to the network interface. The 12
+threads and socket binding should ensure maximum memory access bandwidth
+and minimize communication, migration and numa effect overheads.
+
+Important! Bind every OpenMP thread to a core!
+
+In the previous two cases with one or two MPI processes per node, the
+operating system might still migrate OpenMP threads between cores. You
+want to avoid this by setting the KMP_AFFINITY or GOMP_CPU_AFFINITY
+environment variables.
+
+**24 MPI** processes per node, using 1 thread each bound to processor
+core is most suitable for highly scalable applications with low
+communication demand.
+
+### Running OpenMPI
+
+The [**OpenMPI 1.8.6**](http://www.open-mpi.org/) is
+based on OpenMPI. Read more on [how to run
+OpenMPI](Running_OpenMPI.html) based MPI.
+
+Â
+
+The Intel MPI may run on the[Intel Xeon
+Ph](../intel-xeon-phi.html)i accelerators as well. Read
+more on [how to run Intel MPI on
+accelerators](../intel-xeon-phi.html).
+
diff --git a/converted/docs.it4i.cz/salomon/software/mpi-1/mpi4py-mpi-for-python.md b/converted/docs.it4i.cz/salomon/software/mpi-1/mpi4py-mpi-for-python.md
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+MPI4Py (MPI for Python)
+=======================
+
+OpenMPI interface to Python
+
+
+
+Introduction
+------------
+
+MPI for Python provides bindings of the Message Passing Interface (MPI)
+standard for the Python programming language, allowing any Python
+program to exploit multiple processors.
+
+This package is constructed on top of the MPI-1/2 specifications and
+provides an object oriented interface which closely follows MPI-2 C++
+bindings. It supports point-to-point (sends, receives) and collective
+(broadcasts, scatters, gathers) communications of any picklable Python
+object, as well as optimized communications of Python object exposing
+the single-segment buffer interface (NumPy arrays, builtin
+bytes/string/array objects).
+
+On Anselm MPI4Py is available in standard Python modules.
+
+Modules
+-------
+
+MPI4Py is build for OpenMPI. Before you start with MPI4Py you need to
+load Python and OpenMPI modules. You can use toolchain, that loads
+Python and OpenMPI at once.
+
+ $ module load Python/2.7.9-foss-2015g
+
+Execution
+---------
+
+You need to import MPI to your python program. Include the following
+line to the python script:
+
+ from mpi4py import MPI
+
+The MPI4Py enabled python programs [execute as any other
+OpenMPI](Running_OpenMPI.html) code.The simpliest way is
+to run
+
+ $ mpiexec python <script>.py
+
+For example
+
+ $ mpiexec python hello_world.py
+
+Examples
+--------
+
+### Hello world!
+
+ from mpi4py import MPI
+
+ comm = MPI.COMM_WORLD
+
+ print "Hello! I'm rank %d from %d running in total..." % (comm.rank, comm.size)
+
+ comm.Barrier() Â # wait for everybody to synchronize
+
+###Collective Communication with NumPy arrays
+
+ from __future__ import division
+ from mpi4py import MPI
+ import numpy as np
+
+ comm = MPI.COMM_WORLD
+
+ print("-"*78)
+ print(" Running on %d cores" % comm.size)
+ print("-"*78)
+
+ comm.Barrier()
+
+ # Prepare a vector of N=5 elements to be broadcasted...
+ N = 5
+ if comm.rank == 0:
+ Â Â A = np.arange(N, dtype=np.float64) Â Â # rank 0 has proper data
+ else:
+ Â Â A = np.empty(N, dtype=np.float64) Â Â # all other just an empty array
+
+ # Broadcast A from rank 0 to everybody
+ comm.Bcast( [A, MPI.DOUBLE] )
+
+ # Everybody should now have the same...
+ print "[%02d] %s" % (comm.rank, A)
+
+Execute the above code as:
+
+ $ qsub -q qexp -l select=4:ncpus=24:mpiprocs=24:ompthreads=1 -I
+
+ $ module load Python/2.7.9-foss-2015g
+
+ $ mpiexec --map-by core --bind-to core python hello_world.py
+
+In this example, we run MPI4Py enabled code on 4 nodes, 24 cores per
+node (total of 96 processes), each python process is bound to a
+different core.
+More examples and documentation can be found on [MPI for Python
+webpage](https://pythonhosted.org/mpi4py/usrman/index.html).
+
diff --git a/converted/docs.it4i.cz/salomon/software/numerical-languages/introduction.md b/converted/docs.it4i.cz/salomon/software/numerical-languages/introduction.md
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@@ -0,0 +1,48 @@
+Numerical languages
+===================
+
+Interpreted languages for numerical computations and analysis
+
+
+
+Introduction
+------------
+
+This section contains a collection of high-level interpreted languages,
+primarily intended for numerical computations.
+
+Matlab
+------
+
+MATLAB®^ is a high-level language and interactive environment for
+numerical computation, visualization, and programming.
+
+ $ module load MATLAB
+ $ matlab
+
+Read more at the [Matlab
+page](matlab.html).
+
+Octave
+------
+
+GNU Octave is a high-level interpreted language, primarily intended for
+numerical computations. The Octave language is quite similar to Matlab
+so that most programs are easily portable.
+
+ $ module load Octave
+ $ octave
+
+Read more at the [Octave page](octave.html).
+
+R
+-
+
+The R is an interpreted language and environment for statistical
+computing and graphics.
+
+ $ module load R
+ $ R
+
+Read more at the [R page](r.html).
+
diff --git a/converted/docs.it4i.cz/salomon/software/numerical-languages/matlab.md b/converted/docs.it4i.cz/salomon/software/numerical-languages/matlab.md
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@@ -0,0 +1,345 @@
+Matlab
+======
+
+
+
+Introduction
+------------
+
+Matlab is available in versions R2015a and R2015b. There are always two
+variants of the release:
+
+- Non commercial or so called EDU variant, which can be used for
+ common research and educational purposes.
+- Commercial or so called COM variant, which can used also for
+ commercial activities. The licenses for commercial variant are much
+ more expensive, so usually the commercial variant has only subset of
+ features compared to the EDU available.
+
+Â
+
+To load the latest version of Matlab load the module
+
+ $ module load MATLAB
+
+By default the EDU variant is marked as default. If you need other
+version or variant, load the particular version. To obtain the list of
+available versions use
+
+ $ module avail MATLAB
+
+If you need to use the Matlab GUI to prepare your Matlab programs, you
+can use Matlab directly on the login nodes. But for all computations use
+Matlab on the compute nodes via PBS Pro scheduler.
+
+If you require the Matlab GUI, please follow the general informations
+about [running graphical
+applications](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html).
+
+Matlab GUI is quite slow using the X forwarding built in the PBS (qsub
+-X), so using X11 display redirection either via SSH or directly by
+xauth (please see the "GUI Applications on Compute Nodes over VNC" part
+[here](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html))
+is recommended.
+
+To run Matlab with GUI, use
+
+ $ matlab
+
+To run Matlab in text mode, without the Matlab Desktop GUI environment,
+use
+
+ $ matlab -nodesktop -nosplash
+
+plots, images, etc... will be still available.
+
+Running parallel Matlab using Distributed Computing Toolbox / Engine
+------------------------------------------------------------------------
+
+Distributed toolbox is available only for the EDU variant
+
+The MPIEXEC mode available in previous versions is no longer available
+in MATLAB 2015. Also, the programming interface has changed. Refer
+to [Release
+Notes](http://www.mathworks.com/help/distcomp/release-notes.html#buanp9e-1).
+
+Delete previously used file mpiLibConf.m, we have observed crashes when
+using Intel MPI.
+
+To use Distributed Computing, you first need to setup a parallel
+profile. We have provided the profile for you, you can either import it
+in MATLAB command line:
+
+ > parallel.importProfile('/apps/all/MATLAB/2015b-EDU/SalomonPBSPro.settings')
+
+ ans =
+
+ SalomonPBSProÂ
+
+Or in the GUI, go to tab HOME -> Parallel -> Manage Cluster
+Profiles..., click Import and navigate to :
+
+/apps/all/MATLAB/2015b-EDU/SalomonPBSPro.settings
+
+With the new mode, MATLAB itself launches the workers via PBS, so you
+can either use interactive mode or a batch mode on one node, but the
+actual parallel processing will be done in a separate job started by
+MATLAB itself. Alternatively, you can use "local" mode to run parallel
+code on just a single node.
+
+### Parallel Matlab interactive session
+
+Following example shows how to start interactive session with support
+for Matlab GUI. For more information about GUI based applications on
+Anselm see [this
+page](../../../get-started-with-it4innovations/accessing-the-clusters/graphical-user-interface/x-window-system/x-window-and-vnc.html).
+
+ $ xhost +
+ $ qsub -I -v DISPLAY=$(uname -n):$(echo $DISPLAY | cut -d ':' -f 2) -A NONE-0-0 -q qexp -l select=1 -l walltime=00:30:00
+ -l feature__matlab__MATLAB=1
+
+This qsub command example shows how to run Matlab on a single node.
+
+The second part of the command shows how to request all necessary
+licenses. In this case 1 Matlab-EDU license and 48 Distributed Computing
+Engines licenses.
+
+Once the access to compute nodes is granted by PBS, user can load
+following modules and start Matlab:Â
+
+ r1i0n17$ module load MATLAB/2015a-EDU
+ r1i0n17$ matlab &
+
+### Parallel Matlab batch job in Local mode
+
+To run matlab in batch mode, write an matlab script, then write a bash
+jobscript and execute via the qsub command. By default, matlab will
+execute one matlab worker instance per allocated core.
+
+ #!/bin/bash
+ #PBS -A PROJECT ID
+ #PBS -q qprod
+ #PBS -l select=1:ncpus=24:mpiprocs=24:ompthreads=1
+
+ # change to shared scratch directory
+ SCR=/scratch/work/user/$USER/$PBS_JOBID
+ mkdir -p $SCR ; cd $SCR || exit
+
+ # copy input file to scratch
+ cp $PBS_O_WORKDIR/matlabcode.m .
+
+ # load modules
+ module load MATLAB/2015a-EDU
+
+ # execute the calculation
+ matlab -nodisplay -r matlabcode > output.out
+
+ # copy output file to home
+ cp output.out $PBS_O_WORKDIR/.
+
+This script may be submitted directly to the PBS workload manager via
+the qsub command. The inputs and matlab script are in matlabcode.m
+file, outputs in output.out file. Note the missing .m extension in the
+matlab -r matlabcodefile call, **the .m must not be included**. Note
+that the **shared /scratch must be used**. Further, it is **important to
+include quit** statement at the end of the matlabcode.m script.
+
+Submit the jobscript using qsub
+
+ $ qsub ./jobscript
+
+### Parallel Matlab Local mode program example
+
+The last part of the configuration is done directly in the user Matlab
+script before Distributed Computing Toolbox is started.
+
+ cluster = parcluster('local')
+
+This script creates scheduler object "cluster" of type "local" that
+starts workers locally.Â
+
+Please note: Every Matlab script that needs to initialize/use matlabpool
+has to contain these three lines prior to calling parpool(sched, ...)
+function.Â
+
+The last step is to start matlabpool with "cluster" object and correct
+number of workers. We have 24 cores per node, so we start 24 workers.
+
+ parpool(cluster,24);
+
+
+ ... parallel code ...
+
+
+ parpool close
+
+The complete example showing how to use Distributed Computing Toolbox in
+local mode is shown here.Â
+
+ cluster = parcluster('local');
+ cluster
+
+ parpool(cluster,24);
+
+ n=2000;
+
+ W = rand(n,n);
+ W = distributed(W);
+ x = (1:n)';
+ x = distributed(x);
+ spmd
+ [~, name] = system('hostname')
+ Â Â Â
+ Â Â Â T = W*x; % Calculation performed on labs, in parallel.
+ Â Â Â Â Â Â Â Â Â Â Â Â % T and W are both codistributed arrays here.
+ end
+ T;
+ whos        % T and W are both distributed arrays here.
+
+ parpool close
+ quit
+
+You can copy and paste the example in a .m file and execute. Note that
+the parpool size should correspond to **total number of cores**
+available on allocated nodes.
+
+### Parallel Matlab Batch job using PBS mode (workers spawned in a separate job)
+
+This mode uses PBS scheduler to launch the parallel pool. It uses the
+SalomonPBSPro profile that needs to be imported to Cluster Manager, as
+mentioned before. This methodod uses MATLAB's PBS Scheduler interface -
+it spawns the workers in a separate job submitted by MATLAB using qsub.
+
+This is an example of m-script using PBS mode:
+
+ cluster = parcluster('SalomonPBSPro');
+ set(cluster, 'SubmitArguments', '-A OPEN-0-0');
+ set(cluster, 'ResourceTemplate', '-q qprod -l select=10:ncpus=24');
+ set(cluster, 'NumWorkers', 240);
+
+ pool = parpool(cluster,240);
+
+ n=2000;
+
+ W = rand(n,n);
+ W = distributed(W);
+ x = (1:n)';
+ x = distributed(x);
+ spmd
+ [~, name] = system('hostname')
+
+ T = W*x; % Calculation performed on labs, in parallel.
+ % T and W are both codistributed arrays here.
+ end
+ whos % T and W are both distributed arrays here.
+
+ % shut down parallel pool
+ delete(pool)
+
+Note that we first construct a cluster object using the imported
+profile, then set some important options, namely : SubmitArguments,
+where you need to specify accounting id, and ResourceTemplate, where you
+need to specify number of nodes to run the job.Â
+
+You can start this script using batch mode the same way as in Local mode
+example.
+
+### Parallel Matlab Batch with direct launch (workers spawned within the existing job)
+
+This method is a "hack" invented by us to emulate the mpiexec
+functionality found in previous MATLAB versions. We leverage the MATLAB
+Generic Scheduler interface, but instead of submitting the workers to
+PBS, we launch the workers directly within the running job, thus we
+avoid the issues with master script and workers running in separate jobs
+(issues with license not available, waiting for the worker's job to
+spawn etc.)
+
+Please note that this method is experimental.
+
+For this method, you need to use SalomonDirect profile, import it
+using [the same way as
+SalomonPBSPro](matlab.html#running-parallel-matlab-using-distributed-computing-toolbox---engine)Â
+
+This is an example of m-script using direct mode:
+
+ parallel.importProfile('/apps/all/MATLAB/2015b-EDU/SalomonDirect.settings')
+ cluster = parcluster('SalomonDirect');
+ set(cluster, 'NumWorkers', 48);
+
+ pool = parpool(cluster, 48);
+
+ n=2000;
+
+ W = rand(n,n);
+ W = distributed(W);
+ x = (1:n)';
+ x = distributed(x);
+ spmd
+ [~, name] = system('hostname')
+
+ T = W*x; % Calculation performed on labs, in parallel.
+ % T and W are both codistributed arrays here.
+ end
+ whos % T and W are both distributed arrays here.
+
+ % shut down parallel pool
+ delete(pool)
+
+### Non-interactive Session and Licenses
+
+If you want to run batch jobs with Matlab, be sure to request
+appropriate license features with the PBS Pro scheduler, at least the "
+-l __feature__matlab__MATLAB=1" for EDU variant of Matlab. More
+information about how to check the license features states and how to
+request them with PBS Pro, please [look
+here](../../../anselm-cluster-documentation/software/isv_licenses.html).
+
+The licensing feature of PBS is currently disabled.
+
+In case of non-interactive session please read the [following
+information](../../../anselm-cluster-documentation/software/isv_licenses.html)
+on how to modify the qsub command to test for available licenses prior
+getting the resource allocation.
+
+### Matlab Distributed Computing Engines start up time
+
+Starting Matlab workers is an expensive process that requires certain
+amount of time. For your information please see the following table:
+
+ |compute nodes|number of workers|start-up time[s]|
+ |---|---|---|
+ |16|384|831|
+ |8|192|807|
+ |4|96|483|
+ |2|48|16|
+
+MATLAB on UV2000Â
+-----------------
+
+UV2000 machine available in queue "qfat" can be used for MATLAB
+computations. This is a SMP NUMA machine with large amount of RAM, which
+can be beneficial for certain types of MATLAB jobs. CPU cores are
+allocated in chunks of 8 for this machine.
+
+You can use MATLAB on UV2000 in two parallel modes :
+
+### Threaded mode
+
+Since this is a SMP machine, you can completely avoid using Parallel
+Toolbox and use only MATLAB's threading. MATLAB will automatically
+detect the number of cores you have allocated and will setÂ
+maxNumCompThreads accordingly and certain
+operations, such as fft, , eig, svd,
+etc. will be automatically run in threads. The advantage of this mode is
+that you don't need to modify your existing sequential codes.
+
+### Local cluster mode
+
+You can also use Parallel Toolbox on UV2000. Use l[ocal cluster
+mode](matlab.html#parallel-matlab-batch-job-in-local-mode),
+"SalomonPBSPro" profile will not work.
+
+Â
+
+Â
+
diff --git a/converted/docs.it4i.cz/salomon/software/numerical-languages/octave.md b/converted/docs.it4i.cz/salomon/software/numerical-languages/octave.md
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index 0000000000000000000000000000000000000000..6bb5f2d8480cd01e620cf6d387803b0e7eca1c46
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@@ -0,0 +1,79 @@
+Octave
+======
+
+
+
+GNU Octave is a high-level interpreted language, primarily intended for
+numerical computations. It provides capabilities for the numerical
+solution of linear and nonlinear problems, and for performing other
+numerical experiments. It also provides extensive graphics capabilities
+for data visualization and manipulation. Octave is normally used through
+its interactive command line interface, but it can also be used to write
+non-interactive programs. The Octave language is quite similar to Matlab
+so that most programs are easily portable. Read more on
+<http://www.gnu.org/software/octave/>***
+
+Two versions of octave are available on the cluster, via module
+
+ Status Version module
+ ------ |---|---|---- --------
+ **Stable** Octave 3.8.2 Octave
+
+Â
+
+ $ module load Octave
+
+The octave on the cluster is linked to highly optimized MKL mathematical
+library. This provides threaded parallelization to many octave kernels,
+notably the linear algebra subroutines. Octave runs these heavy
+calculation kernels without any penalty. By default, octave would
+parallelize to 24 threads. You may control the threads by setting the
+OMP_NUM_THREADS environment variable.
+
+To run octave interactively, log in with ssh -X parameter for X11
+forwarding. Run octave:
+
+ $ octave
+
+To run octave in batch mode, write an octave script, then write a bash
+jobscript and execute via the qsub command. By default, octave will use
+16 threads when running MKL kernels.
+
+ #!/bin/bash
+
+ # change to local scratch directory
+ mkdir -p /scratch/work/user/$USER/$PBS_JOBID
+ cd /scratch/work/user/$USER/$PBS_JOBID || exit
+
+ # copy input file to scratch
+ cp $PBS_O_WORKDIR/octcode.m .
+
+ # load octave module
+ module load Octave
+
+ # execute the calculation
+ octave -q --eval octcode > output.out
+
+ # copy output file to home
+ cp output.out $PBS_O_WORKDIR/.
+
+ #exit
+ exit
+
+This script may be submitted directly to the PBS workload manager via
+the qsub command. The inputs are in octcode.m file, outputs in
+output.out file. See the single node jobscript example in the [Job
+execution
+section](../../resource-allocation-and-job-execution.html).
+
+The octave c compiler mkoctfile calls the GNU gcc 4.8.1 for compiling
+native c code. This is very useful for running native c subroutines in
+octave environment.
+
+$ mkoctfile -v
+
+Octave may use MPI for interprocess communication
+This functionality is currently not supported on the cluster cluster. In
+case you require the octave interface to MPI, please contact our
+[cluster support](https://support.it4i.cz/rt/).
+
diff --git a/converted/docs.it4i.cz/salomon/software/numerical-languages/r.md b/converted/docs.it4i.cz/salomon/software/numerical-languages/r.md
new file mode 100644
index 0000000000000000000000000000000000000000..85e34b69199ad4b1bdb78d498e7c98aa89845b9b
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/numerical-languages/r.md
@@ -0,0 +1,460 @@
+R
+=
+
+
+
+Introduction
+------------
+
+The R is a language and environment for statistical computing and
+graphics. R provides a wide variety of statistical (linear and
+nonlinear modelling, classical statistical tests, time-series analysis,
+classification, clustering, ...) and graphical techniques, and is highly
+extensible.
+
+One of R's strengths is the ease with which well-designed
+publication-quality plots can be produced, including mathematical
+symbols and formulae where needed. Great care has been taken over the
+defaults for the minor design choices in graphics, but the user retains
+full control.
+
+Another convenience is the ease with which the C code or third party
+libraries may be integrated within R.
+
+Extensive support for parallel computing is available within R.
+
+Read more on <http://www.r-project.org/>,
+<http://cran.r-project.org/doc/manuals/r-release/R-lang.html>
+
+Modules
+-------
+
+**The R version 3.1.1 is available on the cluster, along with GUI
+interface Rstudio**
+
+ |Application|Version|module|
+ ------- |---|---|---- ---------------------
+ |**R**|R 3.1.1|R/3.1.1-intel-2015b|
+ |**Rstudio**|Rstudio 0.97|Rstudio|
+
+ $ module load R
+
+Execution
+---------
+
+The R on Anselm is linked to highly optimized MKL mathematical
+library. This provides threaded parallelization to many R kernels,
+notably the linear algebra subroutines. The R runs these heavy
+calculation kernels without any penalty. By default, the R would
+parallelize to 24 threads. You may control the threads by setting the
+OMP_NUM_THREADS environment variable.
+
+### Interactive execution
+
+To run R interactively, using Rstudio GUI, log in with ssh -X parameter
+for X11 forwarding. Run rstudio:
+
+ $ module load Rstudio
+ $ rstudio
+
+### Batch execution
+
+To run R in batch mode, write an R script, then write a bash jobscript
+and execute via the qsub command. By default, R will use 24 threads when
+running MKL kernels.
+
+Example jobscript:
+
+ #!/bin/bash
+
+ # change to local scratch directory
+ cd /lscratch/$PBS_JOBID || exit
+
+ # copy input file to scratch
+ cp $PBS_O_WORKDIR/rscript.R .
+
+ # load R module
+ module load R
+
+ # execute the calculation
+ R CMD BATCH rscript.R routput.out
+
+ # copy output file to home
+ cp routput.out $PBS_O_WORKDIR/.
+
+ #exit
+ exit
+
+This script may be submitted directly to the PBS workload manager via
+the qsub command. The inputs are in rscript.R file, outputs in
+routput.out file. See the single node jobscript example in the [Job
+execution
+section](../../resource-allocation-and-job-execution/job-submission-and-execution.html).
+
+Parallel R
+----------
+
+Parallel execution of R may be achieved in many ways. One approach is
+the implied parallelization due to linked libraries or specially enabled
+functions, as [described
+above](r.html#interactive-execution). In the following
+sections, we focus on explicit parallelization, where parallel
+constructs are directly stated within the R script.
+
+Package parallel
+--------------------
+
+The package parallel provides support for parallel computation,
+including by forking (taken from package multicore), by sockets (taken
+from package snow) and random-number generation.
+
+The package is activated this way:
+
+ $ R
+ > library(parallel)
+
+More information and examples may be obtained directly by reading the
+documentation available in R
+
+ > ?parallel
+ > library(help = "parallel")
+ > vignette("parallel")
+
+Download the package
+[parallell](package-parallel-vignette) vignette.
+
+The forking is the most simple to use. Forking family of functions
+provide parallelized, drop in replacement for the serial apply() family
+of functions.
+
+Forking via package parallel provides functionality similar to OpenMP
+construct
+#omp parallel for
+
+Only cores of single node can be utilized this way!
+
+Forking example:
+
+ library(parallel)
+
+ #integrand function
+ f <- function(i,h) {
+ x <- h*(i-0.5)
+ return (4/(1 + x*x))
+ }
+
+ #initialize
+ size <- detectCores()
+
+ while (TRUE)
+ {
+ #read number of intervals
+ cat("Enter the number of intervals: (0 quits) ")
+ fp<-file("stdin"); n<-scan(fp,nmax=1); close(fp)
+
+ if(n<=0) break
+
+ #run the calculation
+ n <- max(n,size)
+ h <- 1.0/n
+
+ i <- seq(1,n);
+ pi3 <- h*sum(simplify2array(mclapply(i,f,h,mc.cores=size)));
+
+ #print results
+ cat(sprintf("Value of PI %16.14f, diff= %16.14fn",pi3,pi3-pi))
+ }
+
+The above example is the classic parallel example for calculating the
+number π. Note the **detectCores()** and **mclapply()** functions.
+Execute the example as:
+
+ $ R --slave --no-save --no-restore -f pi3p.R
+
+Every evaluation of the integrad function runs in parallel on different
+process.
+
+Package Rmpi
+------------
+
+package Rmpi provides an interface (wrapper) to MPI APIs.
+
+It also provides interactive R slave environment. On the cluster, Rmpi
+provides interface to the
+[OpenMPI](../mpi-1/Running_OpenMPI.html).
+
+Read more on Rmpi at <http://cran.r-project.org/web/packages/Rmpi/>,
+reference manual is available at
+<http://cran.r-project.org/web/packages/Rmpi/Rmpi.pdf>
+
+When using package Rmpi, both openmpi and R modules must be loaded
+
+ $ module load OpenMPI
+ $ module load R
+
+Rmpi may be used in three basic ways. The static approach is identical
+to executing any other MPI programm. In addition, there is Rslaves
+dynamic MPI approach and the mpi.apply approach. In the following
+section, we will use the number π integration example, to illustrate all
+these concepts.
+
+### static Rmpi
+
+Static Rmpi programs are executed via mpiexec, as any other MPI
+programs. Number of processes is static - given at the launch time.
+
+Static Rmpi example:
+
+ library(Rmpi)
+
+ #integrand function
+ f <- function(i,h) {
+ x <- h*(i-0.5)
+ return (4/(1 + x*x))
+ }
+
+ #initialize
+ invisible(mpi.comm.dup(0,1))
+ rank <- mpi.comm.rank()
+ size <- mpi.comm.size()
+ n<-0
+
+ while (TRUE)
+ {
+ #read number of intervals
+ if (rank==0) {
+ cat("Enter the number of intervals: (0 quits) ")
+ fp<-file("stdin"); n<-scan(fp,nmax=1); close(fp)
+ }
+
+ #broadcat the intervals
+ n <- mpi.bcast(as.integer(n),type=1)
+
+ if(n<=0) break
+
+ #run the calculation
+ n <- max(n,size)
+ h <- 1.0/n
+
+ i <- seq(rank+1,n,size);
+ mypi <- h*sum(sapply(i,f,h));
+
+ pi3 <- mpi.reduce(mypi)
+
+ #print results
+ if (rank==0) cat(sprintf("Value of PI %16.14f, diff= %16.14fn",pi3,pi3-pi))
+ }
+
+ mpi.quit()
+
+The above is the static MPI example for calculating the number π. Note
+the **library(Rmpi)** and **mpi.comm.dup()** function calls.
+Execute the example as:
+
+ $ mpirun R --slave --no-save --no-restore -f pi3.R
+
+### dynamic Rmpi
+
+Dynamic Rmpi programs are executed by calling the R directly. OpenMPI
+module must be still loaded. The R slave processes will be spawned by a
+function call within the Rmpi program.
+
+Dynamic Rmpi example:
+
+ #integrand function
+ f <- function(i,h) {
+ x <- h*(i-0.5)
+ return (4/(1 + x*x))
+ }
+
+ #the worker function
+ workerpi <- function()
+ {
+ #initialize
+ rank <- mpi.comm.rank()
+ size <- mpi.comm.size()
+ n<-0
+
+ while (TRUE)
+ {
+ #read number of intervals
+ if (rank==0) {
+ cat("Enter the number of intervals: (0 quits) ")
+ fp<-file("stdin"); n<-scan(fp,nmax=1); close(fp)
+ }
+
+ #broadcat the intervals
+ n <- mpi.bcast(as.integer(n),type=1)
+
+ if(n<=0) break
+
+ #run the calculation
+ n <- max(n,size)
+ h <- 1.0/n
+
+ i <- seq(rank+1,n,size);
+ mypi <- h*sum(sapply(i,f,h));
+
+ pi3 <- mpi.reduce(mypi)
+
+ #print results
+ if (rank==0) cat(sprintf("Value of PI %16.14f, diff= %16.14fn",pi3,pi3-pi))
+ }
+ }
+
+ #main
+ library(Rmpi)
+
+ cat("Enter the number of slaves: ")
+ fp<-file("stdin"); ns<-scan(fp,nmax=1); close(fp)
+
+ mpi.spawn.Rslaves(nslaves=ns)
+ mpi.bcast.Robj2slave(f)
+ mpi.bcast.Robj2slave(workerpi)
+
+ mpi.bcast.cmd(workerpi())
+ workerpi()
+
+ mpi.quit()
+
+The above example is the dynamic MPI example for calculating the number
+Ď€. Both master and slave processes carry out the calculation. Note the
+mpi.spawn.Rslaves(), mpi.bcast.Robj2slave()** and the
+mpi.bcast.cmd()** function calls.
+Execute the example as:
+
+ $ mpirun -np 1 R --slave --no-save --no-restore -f pi3Rslaves.R
+
+Note that this method uses MPI_Comm_spawn (Dynamic process feature of
+MPI-2) to start the slave processes - the master process needs to be
+launched with MPI. In general, Dynamic processes are not well supported
+among MPI implementations, some issues might arise. Also, environment
+variables are not propagated to spawned processes, so they will not see
+paths from modules.
+### mpi.apply Rmpi
+
+mpi.apply is a specific way of executing Dynamic Rmpi programs.
+
+mpi.apply() family of functions provide MPI parallelized, drop in
+replacement for the serial apply() family of functions.
+
+Execution is identical to other dynamic Rmpi programs.
+
+mpi.apply Rmpi example:
+
+ #integrand function
+ f <- function(i,h) {
+ x <- h*(i-0.5)
+ return (4/(1 + x*x))
+ }
+
+ #the worker function
+ workerpi <- function(rank,size,n)
+ {
+ #run the calculation
+ n <- max(n,size)
+ h <- 1.0/n
+
+ i <- seq(rank,n,size);
+ mypi <- h*sum(sapply(i,f,h));
+
+ return(mypi)
+ }
+
+ #main
+ library(Rmpi)
+
+ cat("Enter the number of slaves: ")
+ fp<-file("stdin"); ns<-scan(fp,nmax=1); close(fp)
+
+ mpi.spawn.Rslaves(nslaves=ns)
+ mpi.bcast.Robj2slave(f)
+ mpi.bcast.Robj2slave(workerpi)
+
+ while (TRUE)
+ {
+ #read number of intervals
+ cat("Enter the number of intervals: (0 quits) ")
+ fp<-file("stdin"); n<-scan(fp,nmax=1); close(fp)
+ if(n<=0) break
+
+ #run workerpi
+ i=seq(1,2*ns)
+ pi3=sum(mpi.parSapply(i,workerpi,2*ns,n))
+
+ #print results
+ cat(sprintf("Value of PI %16.14f, diff= %16.14fn",pi3,pi3-pi))
+ }
+
+ mpi.quit()
+
+The above is the mpi.apply MPI example for calculating the number π.
+Only the slave processes carry out the calculation. Note the
+mpi.parSapply(), ** function call. The package
+parallel
+[example](r.html#package-parallel)[above](r.html#package-parallel){.anchor
+may be trivially adapted (for much better performance) to this structure
+using the mclapply() in place of mpi.parSapply().
+
+Execute the example as:
+
+ $ mpirun -np 1 R --slave --no-save --no-restore -f pi3parSapply.R
+
+Combining parallel and Rmpi
+---------------------------
+
+Currently, the two packages can not be combined for hybrid calculations.
+
+Parallel execution
+------------------
+
+The R parallel jobs are executed via the PBS queue system exactly as any
+other parallel jobs. User must create an appropriate jobscript and
+submit via the **qsub**
+
+Example jobscript for [static Rmpi](r.html#static-rmpi)
+parallel R execution, running 1 process per core:
+
+ #!/bin/bash
+ #PBS -q qprod
+ #PBS -N Rjob
+ #PBS -l select=100:ncpus=24:mpiprocs=24:ompthreads=1
+
+ # change to scratch directory
+ SCRDIR=/scratch/work/user/$USER/myjob
+ cd $SCRDIR || exit
+
+ # copy input file to scratch
+ cp $PBS_O_WORKDIR/rscript.R .
+
+ # load R and openmpi module
+ module load R
+ module load OpenMPI
+
+ # execute the calculation
+ mpiexec -bycore -bind-to-core R --slave --no-save --no-restore -f rscript.R
+
+ # copy output file to home
+ cp routput.out $PBS_O_WORKDIR/.
+
+ #exit
+ exit
+
+For more information about jobscripts and MPI execution refer to the
+[Job
+submission](../../resource-allocation-and-job-execution/job-submission-and-execution.html)
+and general [MPI](../mpi-1.html) sections.
+
+Xeon Phi Offload
+----------------
+
+By leveraging MKL, R can accelerate certain computations, most notably
+linear algebra operations on the Xeon Phi accelerator by using Automated
+Offload. To use MKL Automated Offload, you need to first set this
+environment variable before R execution :
+
+ $ export MKL_MIC_ENABLE=1
+
+[Read more about automatic
+offload](../intel-xeon-phi.html)
+
diff --git a/converted/docs.it4i.cz/salomon/software/operating-system.md b/converted/docs.it4i.cz/salomon/software/operating-system.md
new file mode 100644
index 0000000000000000000000000000000000000000..9cadb41ffdceb80ea618038b186e10be74f1752b
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/software/operating-system.md
@@ -0,0 +1,13 @@
+Operating System
+================
+
+The operating system, deployed on Salomon cluster
+
+
+
+The operating system on Salomon is Linux - CentOS 6.6.
+
+The CentOS Linux distribution is a stable, predictable, manageable
+and reproducible platform derived from the sources of Red Hat Enterprise
+Linux (RHEL).
+
diff --git a/converted/docs.it4i.cz/salomon/storage/cesnet-data-storage.md b/converted/docs.it4i.cz/salomon/storage/cesnet-data-storage.md
new file mode 100644
index 0000000000000000000000000000000000000000..22b880420d3c4fcba0b5574ebe1865f4fdb4fa24
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/storage/cesnet-data-storage.md
@@ -0,0 +1,128 @@
+CESNET Data Storage
+===================
+
+
+
+Introduction
+------------
+
+Do not use shared filesystems at IT4Innovations as a backup for large
+amount of data or long-term archiving purposes.
+
+The IT4Innovations does not provide storage capacity for data archiving.
+Academic staff and students of research institutions in the Czech
+Republic can use [CESNET Storage
+service](https://du.cesnet.cz/).
+
+The CESNET Storage service can be used for research purposes, mainly by
+academic staff and students of research institutions in the Czech
+Republic.
+
+User of data storage CESNET (DU) association can become organizations or
+an individual person who is either in the current employment
+relationship (employees) or the current study relationship (students) to
+a legal entity (organization) that meets the “Principles for access to
+CESNET Large infrastructure (Access Policy)”.
+
+User may only use data storage CESNET for data transfer and storage
+which are associated with activities in science, research, development,
+the spread of education, culture and prosperity. In detail see
+“Acceptable Use Policy CESNET Large Infrastructure (Acceptable Use
+Policy, AUP)”.
+
+The service is documented at
+<https://du.cesnet.cz/wiki/doku.php/en/start>. For special requirements
+please contact directly CESNET Storage Department via e-mail
+[du-support(at)cesnet.cz](mailto:du-support@cesnet.cz).
+
+The procedure to obtain the CESNET access is quick and trouble-free.
+
+(source
+[https://du.cesnet.cz/](https://du.cesnet.cz/wiki/doku.php/en/start "CESNET Data Storage"))
+
+CESNET storage access
+---------------------
+
+### Understanding Cesnet storage
+
+It is very important to understand the Cesnet storage before uploading
+data. Please read
+<https://du.cesnet.cz/en/navody/home-migrace-plzen/start> first.
+
+Once registered for CESNET Storage, you may [access the
+storage](https://du.cesnet.cz/en/navody/faq/start) in
+number of ways. We recommend the SSHFS and RSYNC methods.
+
+### SSHFS Access
+
+SSHFS: The storage will be mounted like a local hard drive
+
+The SSHFSÂ provides a very convenient way to access the CESNET Storage.
+The storage will be mounted onto a local directory, exposing the vast
+CESNET Storage as if it was a local removable harddrive. Files can be
+than copied in and out in a usual fashion.
+
+First, create the mountpoint
+
+ $ mkdir cesnet
+
+Mount the storage. Note that you can choose among the ssh.du1.cesnet.cz
+(Plzen), ssh.du2.cesnet.cz (Jihlava), ssh.du3.cesnet.cz (Brno)
+Mount tier1_home **(only 5120M !)**:
+
+ $ sshfs username@ssh.du1.cesnet.cz:. cesnet/
+
+For easy future access from Anselm, install your public key
+
+ $ cp .ssh/id_rsa.pub cesnet/.ssh/authorized_keys
+
+Mount tier1_cache_tape for the Storage VO:
+
+ $ sshfs username@ssh.du1.cesnet.cz:/cache_tape/VO_storage/home/username cesnet/
+
+View the archive, copy the files and directories in and out
+
+ $ ls cesnet/
+ $ cp -a mydir cesnet/.
+ $ cp cesnet/myfile .
+
+Once done, please remember to unmount the storage
+
+ $ fusermount -u cesnet
+
+### Rsync access
+
+Rsync provides delta transfer for best performance, can resume
+interrupted transfers
+
+Rsync is a fast and extraordinarily versatile file copying tool. It is
+famous for its delta-transfer algorithm, which reduces the amount of
+data sent over the network by sending only the differences between the
+source files and the existing files in the destination. Rsync is widely
+used for backups and mirroring and as an improved copy command for
+everyday use.
+
+Rsync finds files that need to be transferred using a "quick check"
+algorithm (by default) that looks for files that have changed in size or
+in last-modified time. Any changes in the other preserved attributes
+(as requested by options) are made on the destination file directly when
+the quick check indicates that the file's data does not need to be
+updated.
+
+More about Rsync at
+<https://du.cesnet.cz/en/navody/rsync/start#pro_bezne_uzivatele>
+
+Transfer large files to/from Cesnet storage, assuming membership in the
+Storage VO
+
+ $ rsync --progress datafile username@ssh.du1.cesnet.cz:VO_storage-cache_tape/.
+ $ rsync --progress username@ssh.du1.cesnet.cz:VO_storage-cache_tape/datafile .
+
+Transfer large directories to/from Cesnet storage, assuming membership
+in the Storage VO
+
+ $ rsync --progress -av datafolder username@ssh.du1.cesnet.cz:VO_storage-cache_tape/.
+ $ rsync --progress -av username@ssh.du1.cesnet.cz:VO_storage-cache_tape/datafolder .
+
+Transfer rates of about 28MB/s can be expected.
+
diff --git a/converted/docs.it4i.cz/salomon/storage/storage.md b/converted/docs.it4i.cz/salomon/storage/storage.md
new file mode 100644
index 0000000000000000000000000000000000000000..b170dd2ff3635cd9064fccc64fb5331b2e83bfdc
--- /dev/null
+++ b/converted/docs.it4i.cz/salomon/storage/storage.md
@@ -0,0 +1,513 @@
+Storage
+=======
+
+
+
+Introduction
+------------
+
+There are two main shared file systems on Salomon cluster, the [HOME](storage.html#home)and [SCRATCH](storage.html#shared-filesystems).
+
+All login and compute nodes may access same data on shared filesystems.
+Compute nodes are also equipped with local (non-shared) scratch, ramdisk
+and tmp filesystems.
+
+Policy (in a nutshell)
+----------------------
+
+Use [ for your most valuable data
+and programs.
+Use [WORK](storage.html#work) for your large project
+files
+Use [TEMP](storage.html#temp) for large scratch data.
+
+Do not use for [archiving](storage.html#archiving)!
+
+Archiving
+-------------
+
+Please don't use shared filesystems as a backup for large amount of data
+or long-term archiving mean. The academic staff and students of research
+institutions in the Czech Republic can use [CESNET storage
+service](../../anselm-cluster-documentation/storage-1/cesnet-data-storage.html),
+which is available via SSHFS.
+
+Shared Filesystems
+----------------------
+
+Salomon computer provides two main shared filesystems, the [
+HOME
+filesystem](storage.html#home-filesystem) and the
+[SCRATCH filesystem](storage.html#scratch-filesystem). The
+SCRATCH filesystem is partitioned to [WORK and TEMP
+workspaces](storage.html#shared-workspaces). The HOME
+filesystem is realized as a tiered NFSÂ disk storage. The SCRATCH
+filesystem is realized as a parallel Lustre filesystem. Both shared file
+systems are accessible via the Infiniband network. Extended ACLs are
+provided on both HOME/SCRATCH filesystems for the purpose of sharing
+data with other users using fine-grained control.
+
+###HOME filesystem
+
+The HOME filesystem is realized as a Tiered filesystem, exported via
+NFS. The first tier has capacity 100TB, second tier has capacity 400TB.
+The filesystem is available on all login and computational nodes. The
+Home filesystem hosts the [HOME
+workspace](storage.html#home).
+
+###SCRATCH filesystem
+
+The architecture of Lustre on Salomon is composed of two metadata
+servers (MDS) and six data/object storage servers (OSS). Accessible
+capacity is 1.69 PB, shared among all users. The SCRATCH filesystem
+hosts the [WORK and TEMP
+workspaces](storage.html#shared-workspaces).
+
+ Configuration of the SCRATCH Lustre storage
+
+
+- SCRATCH Lustre object storage
+
+
+ - Disk array SFA12KX
+ - 540 4TB SAS 7.2krpm disks
+ - 54 OSTs of 10 disks in RAID6 (8+2)
+ - 15 hot-spare disks
+ - 4x 400GB SSD cache
+
+
+
+- SCRATCH Lustre metadata storage
+
+
+ - Disk array EF3015
+ - 12 600GB SAS 15krpm disks
+
+
+
+### Understanding the Lustre Filesystems
+
+(source <http://www.nas.nasa.gov>)
+
+A user file on the Lustre filesystem can be divided into multiple chunks
+(stripes) and stored across a subset of the object storage targets
+(OSTs) (disks). The stripes are distributed among the OSTs in a
+round-robin fashion to ensure load balancing.
+
+When a client (a compute
+node from your job) needs to create
+or access a file, the client queries the metadata server (
+MDS) and the metadata target (
+MDT) for the layout and location of the
+[file's
+stripes](http://www.nas.nasa.gov/hecc/support/kb/Lustre_Basics_224.html#striping).
+Once the file is opened and the client obtains the striping information,
+the MDS is no longer involved in the
+file I/O process. The client interacts directly with the object storage
+servers (OSSes) and OSTs to perform I/O operations such as locking, disk
+allocation, storage, and retrieval.
+
+If multiple clients try to read and write the same part of a file at the
+same time, the Lustre distributed lock manager enforces coherency so
+that all clients see consistent results.
+
+There is default stripe configuration for Salomon Lustre filesystems.
+However, users can set the following stripe parameters for their own
+directories or files to get optimum I/O performance:
+
+1. stripe_size: the size of the chunk in bytes; specify with k, m, or
+ g to use units of KB, MB, or GB, respectively; the size must be an
+ even multiple of 65,536 bytes; default is 1MB for all Salomon Lustre
+ filesystems
+2. stripe_count the number of OSTs to stripe across; default is 1 for
+ Salomon Lustre filesystems one can specify -1 to use all OSTs in
+ the filesystem.
+3. stripe_offset The index of the
+ OST where the first stripe is to be
+ placed; default is -1 which results in random selection; using a
+ non-default value is NOT recommended.
+
+Â
+
+Setting stripe size and stripe count correctly for your needs may
+significantly impact the I/O performance you experience.
+
+Use the lfs getstripe for getting the stripe parameters. Use the lfs
+setstripe command for setting the stripe parameters to get optimal I/O
+performance The correct stripe setting depends on your needs and file
+access patterns.Â
+
+`
+$ lfs getstripe dir|filename
+$ lfs setstripe -s stripe_size -c stripe_count -o stripe_offset dir|filename
+`
+
+Example:
+
+`
+$ lfs getstripe /scratch/work/user/username
+/scratch/work/user/username
+stripe_count: 1 stripe_size: 1048576 stripe_offset: -1
+
+$ lfs setstripe -c -1 /scratch/work/user/username/
+$ lfs getstripe /scratch/work/user/username/
+/scratch/work/user/username/
+stripe_count: -1 stripe_size: 1048576 stripe_offset: -1
+`
+
+In this example, we view current stripe setting of the
+/scratch/username/ directory. The stripe count is changed to all OSTs,
+and verified. All files written to this directory will be striped over
+all (54) OSTs
+
+Use lfs check OSTs to see the number and status of active OSTs for each
+filesystem on Salomon. Learn more by reading the man page
+
+`
+$ lfs check osts
+$ man lfs
+`
+
+### Hints on Lustre Stripping
+
+Increase the stripe_count for parallel I/O to the same file.
+
+When multiple processes are writing blocks of data to the same file in
+parallel, the I/O performance for large files will improve when the
+stripe_count is set to a larger value. The stripe count sets the number
+of OSTs the file will be written to. By default, the stripe count is set
+to 1. While this default setting provides for efficient access of
+metadata (for example to support the ls -l command), large files should
+use stripe counts of greater than 1. This will increase the aggregate
+I/O bandwidth by using multiple OSTs in parallel instead of just one. A
+rule of thumb is to use a stripe count approximately equal to the number
+of gigabytes in the file.
+
+Another good practice is to make the stripe count be an integral factor
+of the number of processes performing the write in parallel, so that you
+achieve load balance among the OSTs. For example, set the stripe count
+to 16 instead of 15 when you have 64 processes performing the writes.
+
+Using a large stripe size can improve performance when accessing very
+large files
+
+Large stripe size allows each client to have exclusive access to its own
+part of a file. However, it can be counterproductive in some cases if it
+does not match your I/O pattern. The choice of stripe size has no effect
+on a single-stripe file.
+
+Read more on
+<http://wiki.lustre.org/manual/LustreManual20_HTML/ManagingStripingFreeSpace.html>
+
+Disk usage and quota commands
+------------------------------------------
+
+User quotas on the Lustre file systems (SCRATCH) can be checked
+and reviewed using following command:
+
+`
+$ lfs quota dir
+`
+
+Example for Lustre SCRATCH directory:
+
+`
+$ lfs quota /scratch
+Disk quotas for user user001 (uid 1234):
+ Filesystem kbytes quota limit grace files quota limit grace
+  /scratch    8    0 100000000000    -    3    0    0    -
+Disk quotas for group user001 (gid 1234):
+ Filesystem kbytes quota limit grace files quota limit grace
+ /scratch    8    0    0    -    3    0    0    -
+`
+
+In this example, we view current quota size limit of 100TB and 8KB
+currently used by user001.
+
+HOME directory is mounted via NFS, so a different command must be used
+to obtain quota information:
+
+ Â $ quota
+
+Example output:
+
+ $ quota
+ Disk quotas for user vop999 (uid 1025):
+ Filesystem blocks quota limit grace files quota limit grace
+ home-nfs-ib.salomon.it4i.cz:/home
+ 28 0 250000000 10 0 500000
+
+To have a better understanding of where the space is exactly used, you
+can use following command to find out.
+
+`
+$ du -hs dir
+`
+
+Example for your HOME directory:
+
+`
+$ cd /home
+$ du -hs * .[a-zA-z0-9]* | grep -E "[0-9]*G|[0-9]*M" | sort -hr
+258M cuda-samples
+15M .cache
+13M .mozilla
+5,5M .eclipse
+2,7M .idb_13.0_linux_intel64_app
+`
+
+This will list all directories which are having MegaBytes or GigaBytes
+of consumed space in your actual (in this example HOME) directory. List
+is sorted in descending order from largest to smallest
+files/directories.
+
+To have a better understanding of previous commands, you can read
+manpages.
+
+`
+$ man lfs
+`
+
+`
+$ man du
+`
+
+Extended Access Control List (ACL)
+----------------------------------
+
+Extended ACLs provide another security mechanism beside the standard
+POSIX ACLs which are defined by three entries (for
+owner/group/others). Extended ACLs have more than the three basic
+entries. In addition, they also contain a mask entry and may contain any
+number of named user and named group entries.
+
+ACLs on a Lustre file system work exactly like ACLs on any Linux file
+system. They are manipulated with the standard tools in the standard
+manner. Below, we create a directory and allow a specific user access.
+
+`
+[vop999@login1.salomon ~]$ umask 027
+[vop999@login1.salomon ~]$ mkdir test
+[vop999@login1.salomon ~]$ ls -ld test
+drwxr-x--- 2 vop999 vop999 4096 Nov 5 14:17 test
+[vop999@login1.salomon ~]$ getfacl test
+# file: test
+# owner: vop999
+# group: vop999
+user::rwx
+group::r-x
+other::---
+
+[vop999@login1.salomon ~]$ setfacl -m user:johnsm:rwx test
+[vop999@login1.salomon ~]$ ls -ld test
+drwxrwx---+ 2 vop999 vop999 4096 Nov 5 14:17 test
+[vop999@login1.salomon ~]$ getfacl test
+# file: test
+# owner: vop999
+# group: vop999
+user::rwx
+user:johnsm:rwx
+group::r-x
+mask::rwx
+other::---
+`
+
+Default ACL mechanism can be used to replace setuid/setgid permissions
+on directories. Setting a default ACL on a directory (-d flag to
+setfacl) will cause the ACL permissions to be inherited by any newly
+created file or subdirectory within the directory. Refer to this page
+for more information on Linux ACL:
+
+[http://www.vanemery.com/Linux/ACL/POSIX_ACL_on_Linux.html ](http://www.vanemery.com/Linux/ACL/POSIX_ACL_on_Linux.html)
+
+Shared Workspaces
+---------------------
+
+###HOME
+
+Users home directories /home/username reside on HOME filesystem.
+Accessible capacity is 0.5PB, shared among all users. Individual users
+are restricted by filesystem usage quotas, set to 250GB per user.
+If 250GB should prove as insufficient for particular user, please
+contact [support](https://support.it4i.cz/rt),
+the quota may be lifted upon request.
+
+The HOME filesystem is intended for preparation, evaluation, processing
+and storage of data generated by active Projects.
+
+The HOMEÂ should not be used to archive data of past Projects or other
+unrelated data.
+
+The files on HOME will not be deleted until end of the [users
+lifecycle](../../get-started-with-it4innovations/obtaining-login-credentials/obtaining-login-credentials.html).
+
+The workspace is backed up, such that it can be restored in case ofÂ
+catasthropic failure resulting in significant data loss. This backup
+however is not intended to restore old versions of user data or to
+restore (accidentaly) deleted files.
+
+HOME workspace
+Accesspoint
+/home/username
+Capacity
+0.5PB
+Throughput
+6GB/s
+User quota
+250GB
+Protocol
+NFS, 2-Tier
+### WORK
+
+The WORK workspace resides on SCRATCH filesystem. Users may create
+subdirectories and files in directories **/scratch/work/user/username**
+and **/scratch/work/project/projectid. **The /scratch/work/user/username
+is private to user, much like the home directory. The
+/scratch/work/project/projectid is accessible to all users involved in
+project projectid. >
+
+The WORK workspace is intended to store users project data as well as
+for high performance access to input and output files. All project data
+should be removed once the project is finished. The data on the WORK
+workspace are not backed up.
+
+Files on the WORK filesystem are **persistent** (not automatically
+deleted) throughout duration of the project.
+
+The WORK workspace is hosted on SCRATCH filesystem. The SCRATCH is
+realized as Lustre parallel filesystem and is available from all login
+and computational nodes. Default stripe size is 1MB, stripe count is 1.
+There are 54 OSTs dedicated for the SCRATCH filesystem.
+
+Setting stripe size and stripe count correctly for your needs may
+significantly impact the I/O performance you experience.
+
+WORK workspace
+Accesspoints
+/scratch/work/user/username
+/scratch/work/user/projectid
+Capacity
+1.6P
+Throughput
+30GB/s
+User quota
+100TB
+Default stripe size
+1MB
+Default stripe count
+1
+Number of OSTs
+54
+Protocol
+Lustre
+### TEMP
+
+The TEMP workspace resides on SCRATCH filesystem. The TEMP workspace
+accesspoint is /scratch/temp. Users may freely create subdirectories
+and files on the workspace. Accessible capacity is 1.6P, shared among
+all users on TEMP and WORK. Individual users are restricted by
+filesystem usage quotas, set to 100TB per user. The purpose of this
+quota is to prevent runaway programs from filling the entire filesystem
+and deny service to other users. >If 100TB should prove as
+insufficient for particular user, please contact
+[support](https://support.it4i.cz/rt), the quota may be
+lifted upon request.Â
+
+The TEMP workspace is intended for temporary scratch data generated
+during the calculation as well as for high performance access to input
+and output files. All I/O intensive jobs must use the TEMP workspace as
+their working directory.
+
+Users are advised to save the necessary data from the TEMP workspace to
+HOME or WORK after the calculations and clean up the scratch files.
+
+Files on the TEMP filesystem that are **not accessed for more than 90
+days** will be automatically **deleted**.
+
+The TEMP workspace is hosted on SCRATCH filesystem. The SCRATCH is
+realized as Lustre parallel filesystem and is available from all login
+and computational nodes. Default stripe size is 1MB, stripe count is 1.
+There are 54 OSTs dedicated for the SCRATCH filesystem.
+
+Setting stripe size and stripe count correctly for your needs may
+significantly impact the I/O performance you experience.
+
+TEMP workspace
+Accesspoint
+/scratch/temp
+Capacity
+1.6P
+Throughput
+30GB/s
+User quota
+100TB
+Default stripe size
+1MB
+Default stripe count
+1
+Number of OSTs
+54
+Protocol
+Lustre
+Â
+
+RAM disk
+--------
+
+Every computational node is equipped with filesystem realized in memory,
+so called RAM disk.
+
+Use RAM disk in case you need really fast access to your data of limited
+size during your calculation.
+Be very careful, use of RAM disk filesystem is at the expense of
+operational memory.
+
+The local RAM disk is mounted as /ramdisk and is accessible to user
+at /ramdisk/$PBS_JOBID directory.
+
+The local RAM disk filesystem is intended for temporary scratch data
+generated during the calculation as well as for high performance access
+to input and output files. Size of RAM disk filesystem is limited. Be
+very careful, use of RAM disk filesystem is at the expense of
+operational memory. It is not recommended to allocate large amount of
+memory and use large amount of data in RAM disk filesystem at the same
+time.
+
+The local RAM disk directory /ramdisk/$PBS_JOBID will be deleted
+immediately after the calculation end. Users should take care to save
+the output data from within the jobscript.
+
+RAM disk
+Mountpoint
+ /ramdisk
+Accesspoint
+ /ramdisk/$PBS_JOBID
+Capacity
+120 GB
+Throughput
+over 1.5 GB/s write, over 5 GB/s read, single thread
+over 10 GB/s write, over 50 GB/s read, 16 threads
+
+User quota
+none
+Â
+
+Summary
+
+----------
+
+ --------------------------------------------------
+ |Mountpoint|Usage|Protocol|Net|Capacity|Throughput|Limitations|Access|
+ ---------------------------------------- |---|---|---------------------- ------------- -------------- ------------ ------------- ---------- |**Version**|**Module**|------
+ | /home|home directory|NFS, 2-Tier|0.5 PB|6 GB/s|Quota 250GB|Compute and login nodes|backed up|
+
+ |/scratch/work|large project files|Lustre|1.69 PB|30 GB/s|Quota|Compute and login nodes|none|
+
+
+ |/scratch/temp|job temporary data|Lustre|1.69 PB|30 GB/s|Quota 100TB|Compute and login nodes|files older 90 days removed|
+
+ |/ramdisk|job temporary data, node local|local|120GB|90 GB/s|none|Compute nodes|purged after job ends|
+ --------------------------------------------------
+
+Â
+
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