Merge branch 'preview' into merge-preview-in-main

doc.zih.tu-dresden.de/docs/access/desktop_cloud_visualization.md

@@ -29,7 +29,7 @@ Click on the `DCV` button. A new tab with the DCV client will be opened.
 - Check GPU support via:
 
 ```console hl_lines="4"
-marie@compute$ glxinfo
+marie@compute$ glxinfo | head
 name of display: :1
 display: :1  screen: 0
 direct rendering: Yes

doc.zih.tu-dresden.de/docs/jobs_and_resources/slurm.md

@@ -79,7 +79,7 @@ There are three basic Slurm commands for job submission and execution:
 1. `salloc`: Obtain a Slurm job allocation (i.e., resources like CPUs, nodes and GPUs) for
 interactive use. Release the allocation when finished.
 
-Using `srun` directly on the shell will be blocking and launch an
+Executing a program with `srun` directly on the shell will be blocking and launch an
 [interactive job](#interactive-jobs). Apart from short test runs, it is recommended to submit your
 jobs to Slurm for later execution by using [batch jobs](#batch-jobs). For that, you can conveniently
 put the parameters in a [job file](#job-files), which you can submit using `sbatch
@@ -94,7 +94,7 @@ can find it via `squeue --me`. The job ID allows you to
 
     On ZIH systems, `srun` is used to run your parallel application. The use of `mpirun` is provenly
     broken on partitions `ml` and `alpha` for jobs requiring more than one node. Especially when
-    using code from github projects, double-check it's configuration by looking for a line like
+    using code from github projects, double-check its configuration by looking for a line like
     'submit command  mpirun -n $ranks ./app' and replace it with 'srun ./app'.
 
     Otherwise, this may lead to wrong resource distribution and thus job failure, or tremendous
@@ -196,7 +196,7 @@ marie@compute$ srun --overlap hostname
 taurusi6604.taurus.hrsk.tu-dresden.de
 ```
 
-!!! note "Using `module` commands"
+!!! note "Using `module` commands in interactive mode"
 
     The [module commands](../software/modules.md) are made available by sourcing the files
     `/etc/profile` and `~/.bashrc`. This is done automatically by passing the parameter `-l` to your
@@ -229,7 +229,7 @@ marie@login$ srun --ntasks=1 --pty --x11=first xeyes
 
     that probably means you still have an old host key for the target node in your
     `~.ssh/known_hosts` file (e.g. from pre-SCS5). This can be solved either by removing the entry
-    from your known_hosts or by simply deleting the `known_hosts` file altogether if you don't have
+    from your `known_hosts` or by simply deleting the `known_hosts` file altogether if you don't have
     important other entries in it.
 
 ## Batch Jobs
@@ -335,7 +335,7 @@ marie@login$ srun ./my_application <args for master tasks> : ./my_application <a
 ```
 
 Heterogeneous jobs can also be defined in job files. There, it is required to separate multiple
-components by a line containing the directive `"#SBATCH hetjob`.
+components by a line containing the directive `#SBATCH hetjob`.
 
 ```bash
 #!/bin/bash
@@ -374,7 +374,7 @@ On the command line, use `squeue` to watch the scheduling queue.
 
     Invoke `squeue --me` to list only your jobs.
 
-In it's last column, the `squeue` command will also tell why a job is not running.
+In its last column, the `squeue` command will also tell why a job is not running.
 Possible reasons and their detailed descriptions are listed in the following table.
 More information about job parameters can be obtained with `scontrol -d show
 job <jobid>`.

doc.zih.tu-dresden.de/docs/software/compilers.md

@@ -2,16 +2,17 @@
 
 The following compilers are available on the ZIH system:
 
-|                      | GNU Compiler Collection | Intel Compiler | PGI Compiler (Nvidia HPC SDK) |
-|----------------------|-----------|------------|-------------|
-| Further information  | [GCC website](https://gcc.gnu.org/) | [C/C++](https://software.intel.com/en-us/c-compilers), [Fortran](https://software.intel.com/en-us/fortran-compilers) | [PGI website](https://www.pgroup.com) |
-| Module name          | GNU        | intel     | PGI         |
-| C Compiler           | `gcc`      | `icc`     | `pgcc`      |
-| C++ Compiler         | `g++`      | `icpc`    | `pgc++`     |
-| Fortran Compiler     | `gfortran` | `ifort`   | `pgfortran` |
+|                      | GNU Compiler Collection | Clang Compiler | Intel Compiler | PGI Compiler (Nvidia HPC SDK) |
+|----------------------|-------------------------|----------------|----------------|-------------------------------|
+| Further information  | [GCC website](https://gcc.gnu.org/) | [Clang documentation](https://clang.llvm.org/docs/UsersManual.html) | [C/C++](https://software.intel.com/en-us/c-compilers), [Fortran](https://software.intel.com/en-us/fortran-compilers) | [PGI website](https://www.pgroup.com) |
+| Module name          | GCC        | Clang      | iccifort  | PGI         |
+| C Compiler           | `gcc`      | `clang`    | `icc`     | `pgcc`      |
+| C++ Compiler         | `g++`      | `clang++`  | `icpc`    | `pgc++`     |
+| Fortran Compiler     | `gfortran` |     -      | `ifort`   | `pgfortran` |
 
 For an overview of the installed compiler versions, please use `module spider <module name>`
 on the ZIH systems.
+Additionally you can use `module av` and look below "compilers" to see all available compiler modules.
 
 All compilers support various language standards, at least up to ISO C11, ISO C++ 2014, and Fortran 2003.
 Please check the man pages to verify that your code can be compiled.

doc.zih.tu-dresden.de/docs/software/modules.md

@@ -129,7 +129,7 @@ marie@compute$ module load modenv/ml
 ### modenv/scs5 (default)
 
 * SCS5 software
-* usually optimized for Intel processors (Partitions: `haswell`, `broadwell`, `gpu2`, `julia`)
+* usually optimized for Intel processors (partitions `haswell`, `broadwell`, `gpu2`, `julia`)
 
 ### modenv/ml
 
@@ -142,7 +142,7 @@ Thus the 'machine code' of other modenvs breaks).
 ### modenv/hiera
 
 * uses a hierarchical module load scheme
-* optimized software for AMD processors (Partitions: romeo, alpha)
+* optimized software for AMD processors (partitions `romeo` and `alpha`)
 
 ### modenv/classic
 

doc.zih.tu-dresden.de/docs/software/mpi_usage_error_detection.md

@@ -79,8 +79,11 @@ MUST aware of this knowledge. Overhead is drastically reduced with this switch.
 
 After running your application with MUST you will have its output in the working directory of your
 application. The output is named `MUST_Output.html`. Open this files in a browser to analyze the
-results. The HTML file is color coded: Entries in green represent notes and useful information.
-Entries in yellow represent warnings, and entries in red represent errors.
+results. The HTML file is color coded:
+
+-   Entries in green represent notes and useful information
+-   Entries in yellow represent warnings
+-   Entries in red represent errors
 
 ## Further MPI Correctness Tools
 

doc.zih.tu-dresden.de/docs/software/python_virtual_environments.md

@@ -68,8 +68,8 @@ the environment as follows:
 
 ??? example
 
-    This is an example on partition `alpha`. The example creates a conda virtual environment, and
-    installs the package `torchvision` with conda.
+    This is an example on partition `alpha`. The example creates a python virtual environment, and
+    installs the package `torchvision` with pip.
     ```console
     marie@login$ srun --partition=alpha-interactive --nodes=1 --gres=gpu:1 --time=01:00:00 --pty bash
     marie@alpha$ ws_allocate -F scratch my_python_virtualenv 100    # use a workspace for the environment

doc.zih.tu-dresden.de/docs/software/tensorflow.md

@@ -74,9 +74,9 @@ import TensorFlow:
     [...]
     marie@ml$ which python    #check which python are you using
     /sw/installed/Python/3.7.2-GCCcore-8.2.0
-    marie@ml$ virtualenv --system-site-packages /scratch/ws/1/python_virtual_environment/env
+    marie@ml$ virtualenv --system-site-packages /scratch/ws/1/marie-python_virtual_environment/env
     [...]
-    marie@ml$ source /scratch/ws/1/python_virtual_environment/env/bin/activate
+    marie@ml$ source /scratch/ws/1/marie-python_virtual_environment/env/bin/activate
     marie@ml$ python -c "import tensorflow as tf; print(tf.__version__)"
     [...]
     2.3.1