revision

docs.it4i/anselm-cluster-documentation/software/chemistry/nwchem.md

 # 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.

docs.it4i/anselm-cluster-documentation/software/debuggers/allinea-ddt.md

@@ -48,8 +48,8 @@ $ mpif90 -g -O0 -o test_debug test.f
 Before debugging, you need to compile your code with theses flags:
 
 !!! note
-    - **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.
+    \* **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 DDT
 

docs.it4i/anselm-cluster-documentation/software/debuggers/total-view.md

 # Total View
 
-\##TotalView is a GUI-based source code multi-process, multi-thread debugger.
+TotalView is a GUI-based source code multi-process, multi-thread debugger.
 
 ## License and Limitations for Anselm Users
 
@@ -58,8 +58,8 @@ Compile the code:
 Before debugging, you need to compile your code with theses flags:
 
 !!! note
-    - **-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.
+    \* **-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
 

docs.it4i/anselm-cluster-documentation/software/intel-xeon-phi.md

@@ -632,7 +632,7 @@ The output should be similar to:
 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**
+#### Execution on coprocessor
 
 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.
 
@@ -651,8 +651,8 @@ Similarly to execution of OpenMP programs in native mode, since the environmenta
 ```
 
 !!! note
-    - this file sets up both environmental variable for both MPI and OpenMP libraries.
-    - 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.
+    \* this file sets up both environmental variable for both MPI and OpenMP libraries.
+    \* 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:
 
@@ -681,7 +681,7 @@ The output should be similar to:
     Hello world from process 0 of 4 on host cn207-mic0
 ```
 
-**Execution on host**
+#### 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".
 
@@ -704,8 +704,8 @@ or using mpirun
 ```
 
 !!! note
-    - the full path to the binary has to specified (here: `>~/mpi-test-mic`)
-    - the `LD_LIBRARY_PATH` has to match with Intel MPI module used to compile the MPI code
+    \* the full path to the binary has to specified (here: `>~/mpi-test-mic`)
+    \* the `LD_LIBRARY_PATH` has to match with Intel MPI module used to compile the MPI code
 
 The output should be again similar to:
 
@@ -726,7 +726,7 @@ A simple test to see if the file is present is to execute:
       /bin/pmi_proxy
 ```
 
-**Execution on host - MPI processes distributed over multiple accelerators on multiple nodes**
+#### 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:
 

docs.it4i/anselm-cluster-documentation/software/isv_licenses.md

@@ -69,7 +69,7 @@ Names of applications (APP):
 
 To get the FEATUREs of a license take a look into the corresponding state file ([see above](isv_licenses/#Licence)), or use:
 
-**Application and List of provided features**
+### Application and List of provided features
 
 * **ansys** $ grep -v "#" /apps/user/licenses/ansys_features_state.txt | cut -f1 -d' '
 * **comsol** $ grep -v "#" /apps/user/licenses/comsol_features_state.txt | cut -f1 -d' '

docs.it4i/anselm-cluster-documentation/software/nvidia-cuda.md

 # NVIDIA CUDA
 
-## Guide to NVIDIA CUDA Programming and GPU Usage
+Guide to NVIDIA CUDA Programming and GPU Usage
 
 ## CUDA Programming on Anselm
 
@@ -198,7 +198,7 @@ To run the code use interactive PBS session to get access to one of the GPU acce
 
 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**
+#### 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.