diff --git a/docs.it4i/anselm/capacity-computing.md b/docs.it4i/anselm/capacity-computing.md
index 71b31ab1f55bc8a407e1f2489b1d9f059d735f65..4871b197b048acf20686c990ec5129c6cdf1712c 100644
--- a/docs.it4i/anselm/capacity-computing.md
+++ b/docs.it4i/anselm/capacity-computing.md
@@ -9,13 +9,14 @@ However, executing a huge number of jobs via the PBS queue may strain the system
!!! note
Please follow one of the procedures below, in case you wish to schedule more than 100 jobs at a time.
-* Use [Job arrays](anselm/capacity-computing/#job-arrays) when running a huge number of [multithread](anselm/capacity-computing/#shared-jobscript-on-one-node) (bound to one node only) or multinode (multithread across several nodes) jobs
-* Use [GNU parallel](anselm/capacity-computing/#gnu-parallel) when running single core jobs
-* Combine [GNU parallel with Job arrays](anselm/capacity-computing/#job-arrays-and-gnu-parallel) when running huge number of single core jobs
+* Use [Job arrays][1] when running a huge number of [multithread][2] (bound to one node only) or multinode (multithread across several nodes) jobs
+* Use [GNU parallel][3] when running single core jobs
+* Combine [GNU parallel with Job arrays][4] 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](anselm/capacity-computing/#job-arrays).
+1. A user is allowed to submit at most 100 jobs. Each job may be [a job array][1].
1. The array size is at most 1000 subjobs.
## Job Arrays
@@ -76,7 +77,7 @@ If running a huge number of parallel multicore (in means of multinode multithrea
### Submit the Job Array
-To submit the job array, use the qsub -J command. The 900 jobs of the [example above](anselm/capacity-computing/#array_example) may be submitted like this:
+To submit the job array, use the qsub -J command. The 900 jobs of the [example above][5] may be submitted like this:
```console
$ qsub -N JOBNAME -J 1-900 jobscript
@@ -145,7 +146,7 @@ Display status information for all user's subjobs.
$ qstat -u $USER -tJ
```
-Read more on job arrays in the [PBSPro Users guide](pbspro/).
+Read more on job arrays in the [PBSPro Users guide][6].
## GNU Parallel
@@ -207,7 +208,7 @@ In this example, tasks from the tasklist are executed via the GNU parallel. The
### Submit the Job
-To submit the job, use the qsub command. The 101 task job of the [example above](anselm/capacity-computing/#gp_example) may be submitted as follows:
+To submit the job, use the qsub command. The 101 task job of the [example above][7] may be submitted as follows:
```console
$ qsub -N JOBNAME jobscript
@@ -292,7 +293,7 @@ When deciding this values, keep in mind the following guiding rules:
### Submit the Job Array (-J)
-To submit the job array, use the qsub -J command. The 992 task job of the [example above](anselm/capacity-computing/#combined_example) may be submitted like this:
+To submit the job array, use the qsub -J command. The 992 task job of the [example above][8] may be submitted like this:
```console
$ qsub -N JOBNAME -J 1-992:32 jobscript
@@ -306,7 +307,7 @@ In this example, we submit a job array of 31 subjobs. Note the -J 1-992:**32**,
## Examples
-Download the examples in [capacity.zip](capacity.zip), illustrating the above listed ways to run a huge number of jobs. We recommend trying out the examples before using this for running production jobs.
+Download the examples in [capacity.zip][9], illustrating the above listed ways to run a huge number of jobs. We recommend trying 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
@@ -314,3 +315,13 @@ Unzip the archive in an empty directory on Anselm and follow the instructions in
$ unzip capacity.zip
$ cat README
```
+
+[1]: ./#job-arrays
+[2]: ./#shared-jobscript-on-one-node
+[3]: ./#gnu-parallel
+[4]: ./#job-arrays-and-gnu-parallel
+[5]: ./#array_example
+[6]: ../pbspro.md
+[7]: ./#gp_example
+[8]: ./#combined_example
+[9]: ./capacity.zip
diff --git a/docs.it4i/anselm/compute-nodes.md b/docs.it4i/anselm/compute-nodes.md
index a52810e60eb2dc2daa16b56b9e15e904d1a80018..8b041b31ca24743256a34a4d9dd4a21e727f5c69 100644
--- a/docs.it4i/anselm/compute-nodes.md
+++ b/docs.it4i/anselm/compute-nodes.md
@@ -2,7 +2,7 @@
## Node Configuration
-Anselm is cluster of x86-64 Intel based nodes built with Bull Extreme Computing bullx technology. The cluster contains four types of compute nodes.
+Anselm is a cluster of x86-64 Intel based nodes built with Bull Extreme Computing bullx technology. The cluster contains four types of compute nodes.
### Compute Nodes Without Accelerators
@@ -52,7 +52,7 @@ Anselm is cluster of x86-64 Intel based nodes built with Bull Extreme Computing
### Compute Node Summary
-| Node type | Count | Range | Memory | Cores | [Access](general/resources-allocation-policy/) |
+| Node type | Count | Range | Memory | Cores | Queues |
| ---------------------------- | ----- | ----------- | ------ | ----------- | -------------------------------------- |
| Nodes without an accelerator | 180 | cn[1-180] | 64GB | 16 @ 2.4GHz | qexp, qprod, qlong, qfree, qprace, qatlas |
| Nodes with a GPU accelerator | 23 | cn[181-203] | 96GB | 16 @ 2.3GHz | qnvidia, qexp |
diff --git a/docs.it4i/anselm/hardware-overview.md b/docs.it4i/anselm/hardware-overview.md
index efcff8068431e648cfa8d0edf6e7c021c9d24153..36539dc969a9482ee1ce2fc1b6a3591b1cf3ac72 100644
--- a/docs.it4i/anselm/hardware-overview.md
+++ b/docs.it4i/anselm/hardware-overview.md
@@ -2,7 +2,7 @@
The Anselm cluster consists of 209 computational nodes named cn[1-209] of which 180 are regular compute nodes, 23 are GPU Kepler K20 accelerated nodes, 4 are MIC Xeon Phi 5110P accelerated nodes, and 2 are fat nodes. Each node is a powerful x86-64 computer, equipped with 16 cores (two eight-core Intel Sandy Bridge processors), at least 64 GB of RAM, and a local hard drive. User access to the Anselm cluster is provided by two login nodes login[1,2]. The nodes are interlinked through high speed InfiniBand and Ethernet networks. All nodes share a 320 TB /home disk for storage of user files. The 146 TB shared /scratch storage is available for scratch data.
-The Fat nodes are equipped with a large amount (512 GB) 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) from a PI.
+The Fat nodes are equipped with a large amount (512 GB) 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][a] from a PI.
Schematic representation of the Anselm cluster. Each box represents a node (computer) or storage capacity:
@@ -17,16 +17,16 @@ There are four types of compute nodes:
* 4 compute nodes with a MIC accelerator - an Intel Xeon Phi 5110P
* 2 fat nodes - equipped with 512 GB of RAM and two 100 GB SSD drives
-[More about Compute nodes](anselm/compute-nodes/).
+[More about Compute nodes][1].
-GPU and accelerated nodes are available upon request, see the [Resources Allocation Policy](anselm/resources-allocation-policy/).
+GPU and accelerated nodes are available upon request, see the [Resources Allocation Policy][2].
-All of these nodes are interconnected through fast InfiniBand and Ethernet networks. [More about the Network](anselm/network/).
+All of these nodes are interconnected through fast InfiniBand and Ethernet networks. [More about the Network][3].
Every chassis provides an InfiniBand switch, marked **isw**, connecting all nodes in the chassis, as well as connecting the chassis to the upper level switches.
-All of the nodes share a 360 TB /home disk for storage of user files. The 146 TB shared /scratch storage is available for scratch data. These file systems are provided by the Lustre parallel file system. There is also local disk storage available on all compute nodes in /lscratch. [More about Storage](anselm/storage/).
+All of the nodes share a 360 TB /home disk for storage of user files. The 146 TB shared /scratch storage is available for scratch data. These file systems are provided by the Lustre parallel file system. There is also local disk storage available on all compute nodes in /lscratch. [More about Storage][4].
-User access to the Anselm cluster is provided by two login nodes login1, login2, and data mover node dm1. [More about accessing the cluster.](anselm/shell-and-data-access/)
+User access to the Anselm cluster is provided by two login nodes login1, login2, and data mover node dm1. [More about accessing the cluster][5].
The parameters are summarized in the following tables:
@@ -35,7 +35,7 @@ The parameters are summarized in the following tables:
| Primary purpose | High Performance Computing |
| Architecture of compute nodes | x86-64 |
| Operating system | Linux (CentOS) |
-| [**Compute nodes**](anselm/compute-nodes/) | |
+| [**Compute nodes**][1] | |
| Total | 209 |
| Processor cores | 16 (2 x 8 cores) |
| RAM | min. 64 GB, min. 4 GB per core |
@@ -57,4 +57,12 @@ The parameters are summarized in the following tables:
| MIC accelerated | 2 x Intel Sandy Bridge E5-2470, 2.3 GHz | 96 GB | Intel Xeon Phi 5110P |
| Fat compute node | 2 x Intel Sandy Bridge E5-2665, 2.4 GHz | 512 GB | - |
-For more details refer to [Compute nodes](anselm/compute-nodes/), [Storage](anselm/storage/), and [Network](anselm/network/).
+For more details refer to [Compute nodes][1], [Storage][4], and [Network][3].
+
+[1]: ./compute-nodes.md
+[2]: ./resources-allocation-policy.md
+[3]: ./network.md
+[4]: ./storage.md
+[5]: ./shell-and-data-access.md
+
+[a]: https://support.it4i.cz/rt
diff --git a/docs.it4i/anselm/introduction.md b/docs.it4i/anselm/introduction.md
index 7963784c6dc4cea6838a29c18526d5dc55b343b0..d01c5b06151f43fdb15c361d872ae0b8ee0cbebb 100644
--- a/docs.it4i/anselm/introduction.md
+++ b/docs.it4i/anselm/introduction.md
@@ -1,11 +1,20 @@
# Introduction
-Welcome to Anselm supercomputer cluster. The Anselm cluster consists of 209 compute nodes, totalling 3344 compute cores with 15 TB RAM, giving over 94 TFLOP/s theoretical peak performance. Each node is a powerful x86-64 computer, equipped with 16 cores, at least 64 GB of RAM, and a 500 GB hard disk drive. Nodes are interconnected through a fully non-blocking fat-tree InfiniBand network, and are 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](anselm/hardware-overview/).
+Welcome to Anselm supercomputer cluster. The Anselm cluster consists of 209 compute nodes, totalling 3344 compute cores with 15 TB RAM, giving over 94 TFLOP/s theoretical peak performance. Each node is a powerful x86-64 computer, equipped with 16 cores, at least 64 GB of RAM, and a 500 GB hard disk drive. Nodes are interconnected through a fully non-blocking fat-tree InfiniBand network, and are 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][1].
-The cluster runs with an [operating system](software/operating-system/) 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 packages targeted at different scientific domains. These packages are accessible via the [modules environment](environment-and-modules/).
+The cluster runs with an operating system which is compatible with the RedHat [Linux family][a]. We have installed a wide range of software packages targeted at different scientific domains. These packages are accessible via the [modules environment][2].
The user data shared file-system (HOME, 320 TB) and job data shared file-system (SCRATCH, 146 TB) are available to users.
-The PBS Professional workload manager provides [computing resources allocations and job execution](anselm/resources-allocation-policy/).
+The PBS Professional workload manager provides [computing resources allocations and job execution][3].
-Read more on how to [apply for resources](general/applying-for-resources/), [obtain login credentials](general/obtaining-login-credentials/obtaining-login-credentials/) and [access the cluster](anselm/shell-and-data-access/).
+Read more on how to [apply for resources][4], [obtain login credentials][5] and [access the cluster][6].
+
+[1]: ./hardware-overview.md
+[2]: ../environment-and-modules.md
+[3]: ./resources-allocation-policy.md
+[4]: ../general/applying-for-resources.md
+[5]: ../general/obtaining-login-credentials/obtaining-login-credentials.md
+[6]: ./shell-and-data-access.md
+
+[a]: http://upload.wikimedia.org/wikipedia/commons/1/1b/Linux_Distribution_Timeline.svg