From 32e86ffb1f02a6f7cf19b1d3582144e4f70e3012 Mon Sep 17 00:00:00 2001
From: Martin Schroschk <martin.schroschk@tu-dresden.de>
Date: Tue, 28 Sep 2021 12:52:05 +0200
Subject: [PATCH] Merge, fix links and linter issues
---
doc.zih.tu-dresden.de/docs/jobs_and_resources/slurm.md | 8 +++++---
doc.zih.tu-dresden.de/docs/software/pytorch.md | 4 ++--
doc.zih.tu-dresden.de/docs/software/tensorboard.md | 2 +-
doc.zih.tu-dresden.de/docs/software/tensorflow.md | 2 +-
4 files changed, 9 insertions(+), 7 deletions(-)
diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/slurm.md b/doc.zih.tu-dresden.de/docs/jobs_and_resources/slurm.md
index aef8504d1..606e64e19 100644
--- a/doc.zih.tu-dresden.de/docs/jobs_and_resources/slurm.md
+++ b/doc.zih.tu-dresden.de/docs/jobs_and_resources/slurm.md
@@ -248,7 +248,6 @@ provide a comprehensive collection of job examples.
* Submisson: `marie@login$ sbatch batch_script.sh`
* Run with fewer MPI tasks: `marie@login$ sbatch --ntasks 14 batch_script.sh`
-
## Manage and Control Jobs
### Job and Slurm Monitoring
@@ -321,6 +320,7 @@ We'd like to point your attention to the following options gain insight in your
```console
marie@login$ sacct -j <JOBID>
```
+
??? example "Show all fields for a specific job"
```console
@@ -332,8 +332,9 @@ We'd like to point your attention to the following options gain insight in your
```console
marie@login$ sacct -j <JOBID> -o JobName,MaxRSS,MaxVMSize,CPUTime,ConsumedEnergy
```
-The manual page (`man sacct`) and the [online reference](https://slurm.schedmd.com/sacct.html) provide a
-comprehensive documentation regarding available fields and formats.
+
+The manual page (`man sacct`) and the [online reference](https://slurm.schedmd.com/sacct.html)
+provide a comprehensive documentation regarding available fields and formats.
!!! hint "Time span"
@@ -427,6 +428,7 @@ srun --ntasks 8 --cpus-per-task $OMP_NUM_THREADS ./application
{: align=center}
+
## Node Features for Selective Job Submission
The nodes in our HPC system are becoming more diverse in multiple aspects: hardware, mounted
diff --git a/doc.zih.tu-dresden.de/docs/software/pytorch.md b/doc.zih.tu-dresden.de/docs/software/pytorch.md
index e8e2c4d5e..63d3eb91e 100644
--- a/doc.zih.tu-dresden.de/docs/software/pytorch.md
+++ b/doc.zih.tu-dresden.de/docs/software/pytorch.md
@@ -18,7 +18,7 @@ to find out, which PyTorch modules are available on your partition.
We recommend using **Alpha** and/or **ML** partitions when working with machine learning workflows
and the PyTorch library.
You can find detailed hardware specification in our
-[hardware documentation](../jobs_and_resources/hardware_taurus.md).
+[hardware documentation](../jobs_and_resources/hardware_overview.md).
## PyTorch Console
@@ -44,7 +44,7 @@ Module GCC/10.2.0, CUDA/11.1.1, OpenMPI/4.0.5, PyTorch/1.9.0 and 54 dependencies
marie@alpha$ pip install torchvision --no-deps
```
- Using the **--no-deps** option for "pip install" is necessary here as otherwise the PyTorch
+ Using the **--no-deps** option for "pip install" is necessary here as otherwise the PyTorch
version might be replaced and you will run into trouble with the cuda drivers.
On the **ML** partition:
diff --git a/doc.zih.tu-dresden.de/docs/software/tensorboard.md b/doc.zih.tu-dresden.de/docs/software/tensorboard.md
index a1fab030b..d2c838d39 100644
--- a/doc.zih.tu-dresden.de/docs/software/tensorboard.md
+++ b/doc.zih.tu-dresden.de/docs/software/tensorboard.md
@@ -81,4 +81,4 @@ marie@local$ ssh -N -f -L 6006:taurusi8034.taurus.hrsk.tu-dresden.de:6006 <zih-l
Now, you can see the TensorBoard in your browser at `http://localhost:6006/`.
-Note that you can also use TensorBoard in an [sbatch file](../jobs_and_resources/batch_systems.md).
+Note that you can also use TensorBoard in an [sbatch file](../jobs_and_resources/slurm.md).
diff --git a/doc.zih.tu-dresden.de/docs/software/tensorflow.md b/doc.zih.tu-dresden.de/docs/software/tensorflow.md
index d8ad85c3b..09a8352a3 100644
--- a/doc.zih.tu-dresden.de/docs/software/tensorflow.md
+++ b/doc.zih.tu-dresden.de/docs/software/tensorflow.md
@@ -19,7 +19,7 @@ TensorFlow 2 and TensorFlow 1, see the corresponding [section below](#compatibil
We recommend using partitions **Alpha** and/or **ML** when working with machine learning workflows
and the TensorFlow library. You can find detailed hardware specification in our
-[Hardware](../jobs_and_resources/hardware_taurus.md) documentation.
+[Hardware](../jobs_and_resources/hardware_overview.md) documentation.
## TensorFlow Console
--
GitLab