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	<id>https://wiki.bwhpc.de/wiki/api.php?action=feedcontributions&amp;feedformat=atom&amp;user=M+Kunzelmann</id>
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	<updated>2026-05-25T04:09:23Z</updated>
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	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15912</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15912"/>
		<updated>2026-03-30T18:20:58Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Software Stacks */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login Process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Logout Process =&lt;br /&gt;
&lt;br /&gt;
Your Jupyter Notebook ist started as any other Slurm job.&lt;br /&gt;
If you just close your web browser, the Slurm job will continue to run in the background until it hits the time limit.&lt;br /&gt;
Therefore, you should explicitly stop your server or log out from JupyterHub so that&lt;br /&gt;
* your Slurm job is stopped, and your allocated resources do not count towards your personal and organizational usage quota.&lt;br /&gt;
* resources are returned so that they can be used by others.&lt;br /&gt;
 &lt;br /&gt;
To do this, got to &#039;&#039;&#039;File &amp;gt; Hub Control Panel&#039;&#039;&#039; and click &#039;&#039;&#039;Stop My Server&#039;&#039;&#039;.&lt;br /&gt;
Alternatively, you can also log out via &#039;&#039;&#039;File &amp;gt; Log Out&#039;&#039;&#039;. When you log out, your Jupyter Notebook is also stored.&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
After you logged in via bwIDM, you can select the resources for your Jupyter Notebook.&lt;br /&gt;
&lt;br /&gt;
Preselected are the following values, but you can adjust them as needed:&lt;br /&gt;
* 1 CPU core&lt;br /&gt;
* 16 GB of RAM&lt;br /&gt;
* No GPU&lt;br /&gt;
* Job runtime of 30 minutes&lt;br /&gt;
* Load the &amp;lt;code&amp;gt;jupyter/ai&amp;lt;/code&amp;gt; module (a virtual environment containing libraries typically needed for machine learning)&lt;br /&gt;
* Use the default JupyterHub reservation. From Monday to Friday, from 08:00 to 20:00 o&#039;clock there are four nodes reserved for interactive JupyterHub use. You can still try to start a Juptyer Notebook outside of this time window, however, this job requests is treated as any other job, meaning if the cluster has no available resources the job cannot be started.&lt;br /&gt;
&lt;br /&gt;
When you adjusted your resources, press start and the Notebook is started for you.&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-resource-selection.png|500px]]&lt;br /&gt;
&lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
If you want to use a custom reservation, for example a reservation you previously requested, then un-check the box after &#039;&#039;&#039;Use default reservation&#039;&#039;&#039; and enter your custom reservation name and the token that you received from us.&lt;br /&gt;
You can also try to start the Jupyter Notebook without a custom reservation (and without the default reservation)&lt;br /&gt;
This job is treated as any other by Slurm, meaning it is scheduled if there are available resources.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-custom-reservation.png|500px]]&lt;br /&gt;
&lt;br /&gt;
= Software Stacks = &lt;br /&gt;
&lt;br /&gt;
We provide two Python environments:&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;code&amp;gt;jupyter/minimal&amp;lt;/code&amp;gt;: This Python environment contains just the basic packages to run the Jupyter notebook. You can use this Python environment as base for your own environment, or you can load an environment that you completely build yourself.&lt;br /&gt;
* &amp;lt;code&amp;gt;jupyter/ai&amp;lt;/code&amp;gt; (&#039;&#039;&#039;default&#039;&#039;&#039;): This Python environment is pre-selected in the resource selection dialog. Additional to the minimal environment, it contains &amp;lt;code&amp;gt;plotly, scikit-learn, seaborn, tensorflow, torchvision&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
You can also build and use your own environment in a Jupyter notebook.&lt;br /&gt;
This is a two step process:&lt;br /&gt;
# First you create the Python environment with your required dependencies.&lt;br /&gt;
# Then you make this environment available as kernel for the Jupyter notebook that you can select.&lt;br /&gt;
Take a look at the [[BwUniCluster3.0/Jupyter#Usage_of_virtual_environment_in_JupyterLab|bwUnicluster documentation]].&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an [mailto:dachs-admin@hs-esslingen?Subject=DACHS%20JupyterHub%20Reservation%20Request email] with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15911</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15911"/>
		<updated>2026-03-30T18:17:33Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login Process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Logout Process =&lt;br /&gt;
&lt;br /&gt;
Your Jupyter Notebook ist started as any other Slurm job.&lt;br /&gt;
If you just close your web browser, the Slurm job will continue to run in the background until it hits the time limit.&lt;br /&gt;
Therefore, you should explicitly stop your server or log out from JupyterHub so that&lt;br /&gt;
* your Slurm job is stopped, and your allocated resources do not count towards your personal and organizational usage quota.&lt;br /&gt;
* resources are returned so that they can be used by others.&lt;br /&gt;
 &lt;br /&gt;
To do this, got to &#039;&#039;&#039;File &amp;gt; Hub Control Panel&#039;&#039;&#039; and click &#039;&#039;&#039;Stop My Server&#039;&#039;&#039;.&lt;br /&gt;
Alternatively, you can also log out via &#039;&#039;&#039;File &amp;gt; Log Out&#039;&#039;&#039;. When you log out, your Jupyter Notebook is also stored.&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
After you logged in via bwIDM, you can select the resources for your Jupyter Notebook.&lt;br /&gt;
&lt;br /&gt;
Preselected are the following values, but you can adjust them as needed:&lt;br /&gt;
* 1 CPU core&lt;br /&gt;
* 16 GB of RAM&lt;br /&gt;
* No GPU&lt;br /&gt;
* Job runtime of 30 minutes&lt;br /&gt;
* Load the &amp;lt;code&amp;gt;jupyter/ai&amp;lt;/code&amp;gt; module (a virtual environment containing libraries typically needed for machine learning)&lt;br /&gt;
* Use the default JupyterHub reservation. From Monday to Friday, from 08:00 to 20:00 o&#039;clock there are four nodes reserved for interactive JupyterHub use. You can still try to start a Juptyer Notebook outside of this time window, however, this job requests is treated as any other job, meaning if the cluster has no available resources the job cannot be started.&lt;br /&gt;
&lt;br /&gt;
When you adjusted your resources, press start and the Notebook is started for you.&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-resource-selection.png|500px]]&lt;br /&gt;
&lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
If you want to use a custom reservation, for example a reservation you previously requested, then un-check the box after &#039;&#039;&#039;Use default reservation&#039;&#039;&#039; and enter your custom reservation name and the token that you received from us.&lt;br /&gt;
You can also try to start the Jupyter Notebook without a custom reservation (and without the default reservation)&lt;br /&gt;
This job is treated as any other by Slurm, meaning it is scheduled if there are available resources.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-custom-reservation.png|500px]]&lt;br /&gt;
&lt;br /&gt;
= Software Stacks = &lt;br /&gt;
&lt;br /&gt;
We provide two Python environments:&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;code&amp;gt;jupyter/minimal&amp;lt;/code&amp;gt;: This Python environment contains just the basic packages to run the Jupyter notebook.&lt;br /&gt;
You can use this environment as base for you own environment or use environment that you completely build yourself.&lt;br /&gt;
* &amp;lt;code&amp;gt;jupyter/ai&amp;lt;/code&amp;gt; (default): This Python environment is preselected in the resource selection dialog.&lt;br /&gt;
Additional to the minimal environment, it contains &amp;lt;code&amp;gt;plotly, scikit-learn, seaborn, tensorflow, torchvision&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
You can also build and use your own environment in a Jupyter notebbok.&lt;br /&gt;
First you create the Python environment with your required dependencies.&lt;br /&gt;
Then you make this environment available as kernel for the Jupyter notebook that you can select.&lt;br /&gt;
[[BwUniCluster3.0/Jupyter#Usage_of_virtual_environment_in_JupyterLab|Take a look at the bwUnicluster documentation]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an [mailto:dachs-admin@hs-esslingen?Subject=DACHS%20JupyterHub%20Reservation%20Request email] with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15903</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15903"/>
		<updated>2026-03-24T13:39:50Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Logout Process */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login Process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Logout Process =&lt;br /&gt;
&lt;br /&gt;
Your Jupyter Notebook ist started as any other Slurm job.&lt;br /&gt;
If you just close your web browser, the Slurm job will continue to run in the background until it hits the time limit.&lt;br /&gt;
Therefore, you should explicitly stop your server or log out from JupyterHub so that&lt;br /&gt;
* your Slurm job is stopped, and your allocated resources do not count towards your personal and organizational usage quota.&lt;br /&gt;
* resources are returned so that they can be used by others.&lt;br /&gt;
 &lt;br /&gt;
To do this, got to &#039;&#039;&#039;File &amp;gt; Hub Control Panel&#039;&#039;&#039; and click &#039;&#039;&#039;Stop My Server&#039;&#039;&#039;.&lt;br /&gt;
Alternatively, you can also log out via &#039;&#039;&#039;File &amp;gt; Log Out&#039;&#039;&#039;. When you log out, your Jupyter Notebook is also stored.&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
After you logged in via bwIDM, you can select the resources for your Jupyter Notebook.&lt;br /&gt;
&lt;br /&gt;
Preselected are the following values, but you can adjust them as needed:&lt;br /&gt;
* 1 CPU core&lt;br /&gt;
* 16 GB of RAM&lt;br /&gt;
* No GPU&lt;br /&gt;
* Job runtime of 30 minutes&lt;br /&gt;
* Load the &amp;lt;code&amp;gt;jupyter/ai&amp;lt;/code&amp;gt; module (a virtual environment containing libraries typically needed for machine learning)&lt;br /&gt;
* Use the default JupyterHub reservation. From Monday to Friday, from 08:00 to 20:00 o&#039;clock there are four nodes reserved for interactive JupyterHub use. You can still try to start a Juptyer Notebook outside of this time window, however, this job requests is treated as any other job, meaning if the cluster has no available resources the job cannot be started.&lt;br /&gt;
&lt;br /&gt;
When you adjusted your resources, press start and the Notebook is started for you.&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-resource-selection.png|500px]]&lt;br /&gt;
&lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
If you want to use a custom reservation, for example a reservation you previously requested, then un-check the box after &#039;&#039;&#039;Use default reservation&#039;&#039;&#039; and enter your custom reservation name and the token that you received from us.&lt;br /&gt;
You can also try to start the Jupyter Notebook without a custom reservation (and without the default reservation)&lt;br /&gt;
This job is treated as any other by Slurm, meaning it is scheduled if there are available resources.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-custom-reservation.png|500px]]&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an [mailto:dachs-admin@hs-esslingen?Subject=DACHS%20JupyterHub%20Reservation%20Request email] with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15902</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15902"/>
		<updated>2026-03-24T13:37:56Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Login process */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login Process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Logout Process =&lt;br /&gt;
&lt;br /&gt;
Your Jupyter Notebook ist started as any other Slurm job.&lt;br /&gt;
If you just close your web browser, the Slurm job will continue to run in the background until it hits the time limit.&lt;br /&gt;
Therefore, you should explicitly stop your server or log out from JupyterHub so that&lt;br /&gt;
* your Slurm job is stopped, and your allocated resources do not count towards your personal and organizational usage quota.&lt;br /&gt;
* resources are returned so that they can be used by others.&lt;br /&gt;
 &lt;br /&gt;
To do this, got to &#039;&#039;&#039;File &amp;gt; Hub Control Panel&#039;&#039;&#039; and click &#039;&#039;&#039;Stop My Server&#039;&#039;&#039;.&lt;br /&gt;
Alternatively, you can also log out via &#039;&#039;&#039;File &amp;gt; Logout&#039;&#039;&#039;. When you log out, your Jupyter Notebook is also stored.&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
After you logged in via bwIDM, you can select the resources for your Jupyter Notebook.&lt;br /&gt;
&lt;br /&gt;
Preselected are the following values, but you can adjust them as needed:&lt;br /&gt;
* 1 CPU core&lt;br /&gt;
* 16 GB of RAM&lt;br /&gt;
* No GPU&lt;br /&gt;
* Job runtime of 30 minutes&lt;br /&gt;
* Load the &amp;lt;code&amp;gt;jupyter/ai&amp;lt;/code&amp;gt; module (a virtual environment containing libraries typically needed for machine learning)&lt;br /&gt;
* Use the default JupyterHub reservation. From Monday to Friday, from 08:00 to 20:00 o&#039;clock there are four nodes reserved for interactive JupyterHub use. You can still try to start a Juptyer Notebook outside of this time window, however, this job requests is treated as any other job, meaning if the cluster has no available resources the job cannot be started.&lt;br /&gt;
&lt;br /&gt;
When you adjusted your resources, press start and the Notebook is started for you.&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-resource-selection.png|500px]]&lt;br /&gt;
&lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
If you want to use a custom reservation, for example a reservation you previously requested, then un-check the box after &#039;&#039;&#039;Use default reservation&#039;&#039;&#039; and enter your custom reservation name and the token that you received from us.&lt;br /&gt;
You can also try to start the Jupyter Notebook without a custom reservation (and without the default reservation)&lt;br /&gt;
This job is treated as any other by Slurm, meaning it is scheduled if there are available resources.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-custom-reservation.png|500px]]&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an [mailto:dachs-admin@hs-esslingen?Subject=DACHS%20JupyterHub%20Reservation%20Request email] with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15871</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15871"/>
		<updated>2026-03-24T09:12:20Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Request a Reservation for Your Lecture */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
After you logged in via bwIDM, you can select the resources for your Jupyter Notebook.&lt;br /&gt;
&lt;br /&gt;
Preselected are the following values, but you can adjust them as needed:&lt;br /&gt;
* 1 CPU core&lt;br /&gt;
* 16 GB of RAM&lt;br /&gt;
* No GPU&lt;br /&gt;
* Job runtime of 30 minutes&lt;br /&gt;
* Load the &amp;lt;code&amp;gt;jupyter/ai&amp;lt;/code&amp;gt; module (a virtual environment containing libraries typically needed for machine learning)&lt;br /&gt;
* Use the default JupyterHub reservation. From Monday to Friday, from 08:00 to 20:00 o&#039;clock there are four nodes reserved for interactive JupyterHub use. You can still try to start a Juptyer Notebook outside of this time window, however, this job requests is treated as any other job, meaning if the cluster has no available resources the job cannot be started.&lt;br /&gt;
&lt;br /&gt;
When you adjusted your resources, press start and the Notebook is started for you.&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-resource-selection.png|500px]]&lt;br /&gt;
&lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
If you want to use a custom reservation, for example a reservation you previously requested, then un-check the box after &#039;&#039;&#039;Use default reservation&#039;&#039;&#039; and enter your custom reservation name and the token that you received from us.&lt;br /&gt;
You can also try to start the Jupyter Notebook without a custom reservation (and without the default reservation)&lt;br /&gt;
This job is treated as any other by Slurm, meaning it is scheduled if there are available resources.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-custom-reservation.png|500px]]&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an [mailto:dachs-admin@hs-esslingen?Subject=DACHS%20JupyterHub%20Reservation%20Request email] with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15870</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15870"/>
		<updated>2026-03-24T09:11:09Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Selection of Compute Resources */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
After you logged in via bwIDM, you can select the resources for your Jupyter Notebook.&lt;br /&gt;
&lt;br /&gt;
Preselected are the following values, but you can adjust them as needed:&lt;br /&gt;
* 1 CPU core&lt;br /&gt;
* 16 GB of RAM&lt;br /&gt;
* No GPU&lt;br /&gt;
* Job runtime of 30 minutes&lt;br /&gt;
* Load the &amp;lt;code&amp;gt;jupyter/ai&amp;lt;/code&amp;gt; module (a virtual environment containing libraries typically needed for machine learning)&lt;br /&gt;
* Use the default JupyterHub reservation. From Monday to Friday, from 08:00 to 20:00 o&#039;clock there are four nodes reserved for interactive JupyterHub use. You can still try to start a Juptyer Notebook outside of this time window, however, this job requests is treated as any other job, meaning if the cluster has no available resources the job cannot be started.&lt;br /&gt;
&lt;br /&gt;
When you adjusted your resources, press start and the Notebook is started for you.&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-resource-selection.png|500px]]&lt;br /&gt;
&lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
If you want to use a custom reservation, for example a reservation you previously requested, then un-check the box after &#039;&#039;&#039;Use default reservation&#039;&#039;&#039; and enter your custom reservation name and the token that you received from us.&lt;br /&gt;
You can also try to start the Jupyter Notebook without a custom reservation (and without the default reservation)&lt;br /&gt;
This job is treated as any other by Slurm, meaning it is scheduled if there are available resources.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-custom-reservation.png|500px]]&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an [mailto:dachs-admin@hs-esslingen email] with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15869</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15869"/>
		<updated>2026-03-24T09:08:04Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Selection of Compute Resources */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
After you logged in via bwIDM, you can select the resources for your Jupyter Notebook.&lt;br /&gt;
&lt;br /&gt;
Preselected are the following values, but you can adjust them as needed:&lt;br /&gt;
* 1 CPU core&lt;br /&gt;
* 16 GB of RAM&lt;br /&gt;
* No GPU&lt;br /&gt;
* Job runtime of 30 minutes&lt;br /&gt;
* Load the &amp;lt;code&amp;gt;jupyter/ai&amp;lt;/code&amp;gt; module (a virtual environment containing libraries typically needed for machine learning)&lt;br /&gt;
* Use the default JupyterHub reservation. From Monday to Friday, from 08:00 to 20:00 o&#039;clock there are four nodes reserved for interactive JupyterHub use. You can still try to start a Juptyer Notebook outside of this time window, however, this job requests is treated as any other job, meaning if the cluster has no available resources the job cannot be started.&lt;br /&gt;
&lt;br /&gt;
When you adjusted your resources, press start and the Notebook is started for you.&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-resource-selection.png]]&lt;br /&gt;
&lt;br /&gt;
If you want to use a custom reservation, for example a reservation you previously requests, then un-check the box after &#039;&#039;&#039;Use default reservation&#039;&#039;&#039; and enter your custom reservation name and the token that you received from us.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-custom-reservation.png]]&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an [mailto:dachs-admin@hs-esslingen email] with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=File:20260324-dachs-jupyter-custom-reservation.png&amp;diff=15868</id>
		<title>File:20260324-dachs-jupyter-custom-reservation.png</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=File:20260324-dachs-jupyter-custom-reservation.png&amp;diff=15868"/>
		<updated>2026-03-24T09:07:39Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15867</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15867"/>
		<updated>2026-03-24T09:04:31Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Selection of Compute Resources */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
After you logged in via bwIDM, you can select the resources for your Jupyter Notebook.&lt;br /&gt;
&lt;br /&gt;
Preselected are the following values, but you can adjust them as needed:&lt;br /&gt;
* 1 CPU core&lt;br /&gt;
* 16 GB of RAM&lt;br /&gt;
* No GPU&lt;br /&gt;
* Job runtime of 30 minutes&lt;br /&gt;
* Load the &amp;lt;code&amp;gt;jupyter/ai&amp;lt;/code&amp;gt; module (a virtual environment containing libraries typically needed for machine learning)&lt;br /&gt;
* Use the default JupyterHub reservation. From Monday to Friday, from 08:00 to 20:00 o&#039;clock there are four nodes reserved for interactive JupyterHub use. You can still try to start a Juptyer Notebook outside of this time window, however, this job requests is treated as any other job, meaning if the cluster has no available resources the job cannot be started.&lt;br /&gt;
&lt;br /&gt;
When you adjusted your resources, press start and the Notebook is started for you.&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-resource-selection.png]]&lt;br /&gt;
&lt;br /&gt;
If you want to use a custom reservation, for example a reservation you previously requests, then un-check the box after &#039;&#039;&#039;Use default reservation&#039;&#039;&#039; and enter your custom reservation name and the token that you received from us.&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an [mailto:dachs-admin@hs-esslingen email] with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15866</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15866"/>
		<updated>2026-03-24T08:55:56Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Selection of Compute Resources */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
[[Image:20260324-dachs-jupyter-resource-selection.png]]&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an [mailto:dachs-admin@hs-esslingen email] with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=File:20260324-dachs-jupyter-resource-selection.png&amp;diff=15865</id>
		<title>File:20260324-dachs-jupyter-resource-selection.png</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=File:20260324-dachs-jupyter-resource-selection.png&amp;diff=15865"/>
		<updated>2026-03-24T08:53:36Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15864</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15864"/>
		<updated>2026-03-24T08:49:12Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Request a Reservation for Your Lecture */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an [mailto:dachs-admin@hs-esslingen email] with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15863</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15863"/>
		<updated>2026-03-24T08:48:33Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Request a Reservation for Your Lecture */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an email to [mailto:dachs-admin@hs-esslingen] with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15862</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15862"/>
		<updated>2026-03-24T08:48:05Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Request a Reservation for Your Lecture */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an email to &amp;lt;mailto:dachs-admin@hs-esslingen&amp;gt; with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15861</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15861"/>
		<updated>2026-03-24T08:46:34Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Request a Reservation for Your Lecture */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an email to &amp;lt;mailto:dachs-admin@hs-esslingen&amp;gt; with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[##Selection_of_Compute_Resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15860</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15860"/>
		<updated>2026-03-24T08:46:10Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Selection of the compute resources */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Selection of Compute Resources =&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an email to &amp;lt;mailto:dachs-admin@hs-esslingen&amp;gt; with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#selection-of-compute-resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15859</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15859"/>
		<updated>2026-03-24T08:45:59Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Selection of the compute resources */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Short description of Jupyter =&lt;br /&gt;
Jupyter (an acronym for &#039;&#039;Ju&#039;&#039;lia, &#039;&#039;Py&#039;&#039;thon and &#039;&#039;R&#039;&#039;) is a web application, allowing interactive programming and visualization in a browser. Jupyter uses so-called Jupyter-Notebooks to load and store the program, input data and it&#039;s output (including visualization) in a JSON-based file, allowing exchange between different implementations (like Visual Studio Code plus a Jupyter Extension) and specifically allowing incrementally editing using a version-control system like git.&lt;br /&gt;
&lt;br /&gt;
We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/] as described below.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Access requirements =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to Jupyter is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All partners of DACHS are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect without restrictions. Otherwise, You will see a hint about having to connect using VPN to Your home institution (and make sure, that all packets are routed through your home institution&#039;s VPN, and not in SPLIT tunneling mode, see [[DACHS/Login|Login]] page.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
# Register as described on the [[DACHS/Registration|Registration]]&lt;br /&gt;
# Then [[DACHS/Login|login to DACHS]] via SSH &#039;&#039;&#039;at least once&#039;&#039;&#039;: This ensures that your home directory is setup properly on DACHS&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039; (see above)&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login process =&lt;br /&gt;
After having logged into&lt;br /&gt;
  https://dachs-jupyter.hs-esslingen.de&lt;br /&gt;
You will need to specify the resources, as described in the next section.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Selection of the compute resources =&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Request a Reservation for Your Lecture =&lt;br /&gt;
&lt;br /&gt;
Requesting a unique reservation for JupyterHub has the advantage that the requested resources will be available to you for sure at the time you need them.&lt;br /&gt;
Furthermore, it&#039;s easy:&lt;br /&gt;
&lt;br /&gt;
1. Send an email to &amp;lt;mailto:dachs-admin@hs-esslingen&amp;gt; with the following information:&lt;br /&gt;
* Start time and duration&lt;br /&gt;
* How many nodes do you request? Generally, we assign nodes from the [[ DACHS/Hardware | &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; partition ]] to JupyterHub jobs.&lt;br /&gt;
* Do you request a one-time or periodic reservation?&lt;br /&gt;
* The usernames that should have access to the reservation. This is at least your username. (For example &amp;lt;code&amp;gt;es_username&amp;lt;/code&amp;gt;). If you want the students of your lecture to have access as well, export a list of their usernames and send these as well. We need to know the usernames to assign the correct entitlement to access the resource.&lt;br /&gt;
&lt;br /&gt;
2. Wait for a reply. You&#039;ll get a &#039;&#039;reservation name&#039;&#039; and a &#039;&#039;reservation token&#039;&#039; that must be entered in the [[#selection-of-compute-resources|resource selection]] dialog of JupyterHub.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Hardware&amp;diff=15841</id>
		<title>DACHS/Hardware</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Hardware&amp;diff=15841"/>
		<updated>2026-03-17T17:51:06Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Storage Architecture */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Architecture of DACHS =&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) is a parallel computer with distributed memory connected over Infiniband and Ethernet.&lt;br /&gt;
The compute nodes contain at least dual AMD processors, at least 384GB of local memory, 2 TB local NVMe-based disc storage and accelerators as shown in the table below.&lt;br /&gt;
With BeeGFS, a fast and scalable filesystem is provided via Infiniband to all both login and all compute nodes.&lt;br /&gt;
&lt;br /&gt;
The Operating System is Rocky-Linux 9.5 (which is based on RHEL).&lt;br /&gt;
The setup is kept in-line (with regard to Software, Setup and general usage) and thus mostly equivalent to bwHPC and bwUniCluster in particular.&lt;br /&gt;
&lt;br /&gt;
= Components of DACHS =&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
|- &lt;br /&gt;
! style=&amp;quot;width:9%&amp;quot;|&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;L40S&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;H100&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;AMD_APU&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Login&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Availability in Queue&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt;&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt;&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt;&lt;br /&gt;
|&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Number of nodes&lt;br /&gt;
| 45&lt;br /&gt;
| 1&lt;br /&gt;
| 1&lt;br /&gt;
| 2&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Processors&lt;br /&gt;
| AMD EPYC 9254&lt;br /&gt;
| AMD EPYC 9454&lt;br /&gt;
| AMD MI300A&lt;br /&gt;
| AMD EPYC 9254&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Number of sockets&lt;br /&gt;
| 2&lt;br /&gt;
| 2&lt;br /&gt;
| 4&lt;br /&gt;
| 2&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Processor frequency (GHz)&lt;br /&gt;
| 2.9 Ghz&lt;br /&gt;
| 2.75 Ghz&lt;br /&gt;
| 2.1 Ghz&lt;br /&gt;
| 2.9 Ghz&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Total number of cores&lt;br /&gt;
| 48&lt;br /&gt;
| 96&lt;br /&gt;
| 96&lt;br /&gt;
| 48&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Main memory&lt;br /&gt;
| 384 GB&lt;br /&gt;
| 1536 GB&lt;br /&gt;
| 512 GB&lt;br /&gt;
| 384 GB&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Local SSD&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Accelerators&lt;br /&gt;
| 1x NVIDIA L40S&lt;br /&gt;
| 8x NVIDIA H100&lt;br /&gt;
| 4x AMD MI300A&lt;br /&gt;
| -&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Accelerator memory&lt;br /&gt;
| 48 GB&lt;br /&gt;
| 8x 80 GB&lt;br /&gt;
| 4x 128 GB&lt;br /&gt;
| -&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Interconnect&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
|}&lt;br /&gt;
Table 1: Properties of the nodes&lt;br /&gt;
&lt;br /&gt;
== Storage Architecture ==&lt;br /&gt;
The system features a 700 TB large BeeGFS filesystem available on login and compute nodes.&lt;br /&gt;
Please note: there is a hard file size quota per partner organization and a soft quota per user on Your HOME.&lt;br /&gt;
Users will be notified by E-Mail if the quota is to be reached.&lt;br /&gt;
&lt;br /&gt;
Please &#039;&#039;&#039;make use&#039;&#039;&#039; of the [[Workspaces | Work Space mechanism]] for larger data sets.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Hardware&amp;diff=15840</id>
		<title>DACHS/Hardware</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Hardware&amp;diff=15840"/>
		<updated>2026-03-17T17:50:37Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Storage Architecture */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Architecture of DACHS =&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) is a parallel computer with distributed memory connected over Infiniband and Ethernet.&lt;br /&gt;
The compute nodes contain at least dual AMD processors, at least 384GB of local memory, 2 TB local NVMe-based disc storage and accelerators as shown in the table below.&lt;br /&gt;
With BeeGFS, a fast and scalable filesystem is provided via Infiniband to all both login and all compute nodes.&lt;br /&gt;
&lt;br /&gt;
The Operating System is Rocky-Linux 9.5 (which is based on RHEL).&lt;br /&gt;
The setup is kept in-line (with regard to Software, Setup and general usage) and thus mostly equivalent to bwHPC and bwUniCluster in particular.&lt;br /&gt;
&lt;br /&gt;
= Components of DACHS =&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
|- &lt;br /&gt;
! style=&amp;quot;width:9%&amp;quot;|&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;L40S&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;H100&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;AMD_APU&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Login&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Availability in Queue&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt;&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt;&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt;&lt;br /&gt;
|&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Number of nodes&lt;br /&gt;
| 45&lt;br /&gt;
| 1&lt;br /&gt;
| 1&lt;br /&gt;
| 2&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Processors&lt;br /&gt;
| AMD EPYC 9254&lt;br /&gt;
| AMD EPYC 9454&lt;br /&gt;
| AMD MI300A&lt;br /&gt;
| AMD EPYC 9254&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Number of sockets&lt;br /&gt;
| 2&lt;br /&gt;
| 2&lt;br /&gt;
| 4&lt;br /&gt;
| 2&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Processor frequency (GHz)&lt;br /&gt;
| 2.9 Ghz&lt;br /&gt;
| 2.75 Ghz&lt;br /&gt;
| 2.1 Ghz&lt;br /&gt;
| 2.9 Ghz&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Total number of cores&lt;br /&gt;
| 48&lt;br /&gt;
| 96&lt;br /&gt;
| 96&lt;br /&gt;
| 48&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Main memory&lt;br /&gt;
| 384 GB&lt;br /&gt;
| 1536 GB&lt;br /&gt;
| 512 GB&lt;br /&gt;
| 384 GB&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Local SSD&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Accelerators&lt;br /&gt;
| 1x NVIDIA L40S&lt;br /&gt;
| 8x NVIDIA H100&lt;br /&gt;
| 4x AMD MI300A&lt;br /&gt;
| -&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Accelerator memory&lt;br /&gt;
| 48 GB&lt;br /&gt;
| 8x 80 GB&lt;br /&gt;
| 4x 128 GB&lt;br /&gt;
| -&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Interconnect&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
|}&lt;br /&gt;
Table 1: Properties of the nodes&lt;br /&gt;
&lt;br /&gt;
== Storage Architecture ==&lt;br /&gt;
The system features a 700 TB large BeeGFS filesystem available on login and compute nodes.&lt;br /&gt;
Please note: there is a hard file size quota per partner organization and a soft quota per user on Your HOME.&lt;br /&gt;
Users will be notified by E-Mail if the quota is to be reached.&lt;br /&gt;
&lt;br /&gt;
Please &#039;&#039;&#039;do make use&#039;&#039;&#039; of [[Workspaces | Work Space mechanism]] for larger files.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Hardware&amp;diff=15839</id>
		<title>DACHS/Hardware</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Hardware&amp;diff=15839"/>
		<updated>2026-03-17T17:49:50Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Architecture of DACHS */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Architecture of DACHS =&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) is a parallel computer with distributed memory connected over Infiniband and Ethernet.&lt;br /&gt;
The compute nodes contain at least dual AMD processors, at least 384GB of local memory, 2 TB local NVMe-based disc storage and accelerators as shown in the table below.&lt;br /&gt;
With BeeGFS, a fast and scalable filesystem is provided via Infiniband to all both login and all compute nodes.&lt;br /&gt;
&lt;br /&gt;
The Operating System is Rocky-Linux 9.5 (which is based on RHEL).&lt;br /&gt;
The setup is kept in-line (with regard to Software, Setup and general usage) and thus mostly equivalent to bwHPC and bwUniCluster in particular.&lt;br /&gt;
&lt;br /&gt;
= Components of DACHS =&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
|- &lt;br /&gt;
! style=&amp;quot;width:9%&amp;quot;|&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;L40S&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;H100&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;AMD_APU&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Login&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Availability in Queue&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt;&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt;&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt;&lt;br /&gt;
|&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Number of nodes&lt;br /&gt;
| 45&lt;br /&gt;
| 1&lt;br /&gt;
| 1&lt;br /&gt;
| 2&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Processors&lt;br /&gt;
| AMD EPYC 9254&lt;br /&gt;
| AMD EPYC 9454&lt;br /&gt;
| AMD MI300A&lt;br /&gt;
| AMD EPYC 9254&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Number of sockets&lt;br /&gt;
| 2&lt;br /&gt;
| 2&lt;br /&gt;
| 4&lt;br /&gt;
| 2&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Processor frequency (GHz)&lt;br /&gt;
| 2.9 Ghz&lt;br /&gt;
| 2.75 Ghz&lt;br /&gt;
| 2.1 Ghz&lt;br /&gt;
| 2.9 Ghz&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Total number of cores&lt;br /&gt;
| 48&lt;br /&gt;
| 96&lt;br /&gt;
| 96&lt;br /&gt;
| 48&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Main memory&lt;br /&gt;
| 384 GB&lt;br /&gt;
| 1536 GB&lt;br /&gt;
| 512 GB&lt;br /&gt;
| 384 GB&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Local SSD&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Accelerators&lt;br /&gt;
| 1x NVIDIA L40S&lt;br /&gt;
| 8x NVIDIA H100&lt;br /&gt;
| 4x AMD MI300A&lt;br /&gt;
| -&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Accelerator memory&lt;br /&gt;
| 48 GB&lt;br /&gt;
| 8x 80 GB&lt;br /&gt;
| 4x 128 GB&lt;br /&gt;
| -&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Interconnect&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
|}&lt;br /&gt;
Table 1: Properties of the nodes&lt;br /&gt;
&lt;br /&gt;
== Storage Architecture ==&lt;br /&gt;
The system features a 700 TB large BeeGFS filesystem available on login and compute nodes.&lt;br /&gt;
Please note: there is a hard file size quota per partner organization and a soft quota per user on Your HOME.&lt;br /&gt;
Users will be notified by E-Mail if the quota is to be reached.&lt;br /&gt;
&lt;br /&gt;
Please &#039;&#039;&#039;do make usage&#039;&#039;&#039; of [[Workspace | Work Space mechanism]] for larger files.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Quickstart_Slurm&amp;diff=15682</id>
		<title>DACHS/Quickstart Slurm</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Quickstart_Slurm&amp;diff=15682"/>
		<updated>2026-01-14T13:42:49Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: add sacct command&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&amp;lt;span id=&amp;quot;quickstart&amp;quot;&amp;gt;&amp;lt;/span&amp;gt;&lt;br /&gt;
= Quickstart =&lt;br /&gt;
&lt;br /&gt;
&amp;lt;span id=&amp;quot;contact-and-further-links-to-bwhpc-wiki&amp;quot;&amp;gt;&amp;lt;/span&amp;gt;&lt;br /&gt;
== Contact and Further Links to bwHPC wiki ==&lt;br /&gt;
&lt;br /&gt;
If you don&#039;t find the information you need in this wiki, you can always reach us at [mailto:dachs-admin@hs-esslingen.de dachs-admin@hs-esslingen.de].&lt;br /&gt;
&lt;br /&gt;
&amp;lt;span id=&amp;quot;typical-sbatch-script&amp;quot;&amp;gt;&amp;lt;/span&amp;gt;&lt;br /&gt;
== Typical SBATCH script ==&lt;br /&gt;
&lt;br /&gt;
This is just a brief guide to get you started. All queues, limits, and hardware are documented in detail at the [[DACHS/Hardware]].&lt;br /&gt;
&lt;br /&gt;
Our default queue is &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; that you specify with &amp;lt;code&amp;gt;--partition=gpu1&amp;lt;/code&amp;gt; explicitly. Other queues are &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt; (4 AMD MI300A APUs) and &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt; (8 NVIDIA H100 GPUs). For more deatiled information, visit [https://wiki.bwhpc.de/e/DACHS/Queues DACHS/Queues].&lt;br /&gt;
&lt;br /&gt;
This is the content of &amp;lt;code&amp;gt;testjob.sh&amp;lt;/code&amp;gt;. It is basically a Bash script with some instructions in the format of comment for the Slurm scheduler.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;#!/bin/bash&lt;br /&gt;
#SBATCH --ntasks=1               # allocate 1 CPU&lt;br /&gt;
#SBATCH --time=30:00             # time limit of 30 min&lt;br /&gt;
#SBATCH --mem=42gb               # allocate 42 GB RAM&lt;br /&gt;
#SBATch --gres=gpu:1             # allocate one GPU&lt;br /&gt;
#SBATCH --job-name=&amp;quot;CHANGEME JOBNAME&amp;quot;&lt;br /&gt;
# Uncomment the following lines to get email notifications about your job&lt;br /&gt;
# #SBATCH --mail-type=ALL        # list of &amp;quot;ALL,START,END&lt;br /&gt;
# #SBATCH --mail-user=CHANGME@EMAIL.COM&lt;br /&gt;
&lt;br /&gt;
# You Shell script that setups your job and starts your work is here.&lt;br /&gt;
# That might include loading a module from provided software (check with&lt;br /&gt;
# `module avail` or sourcing a Python environment.&lt;br /&gt;
&lt;br /&gt;
# Load Python 3.13.3 compiled with gnu 14.2&lt;br /&gt;
module load devel/python/3.13.3-gnu-14.2&lt;br /&gt;
&lt;br /&gt;
# Run your Python script that you previously prepared on the Login node.&lt;br /&gt;
uv run python3 main.py&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
For a detailed overview of slurm visit the [https://wiki.bwhpc.de/e/BwUniCluster2.0/Slurm SBATCH options and Slurm wiki page].&lt;br /&gt;
&lt;br /&gt;
You can display available nodes by running&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;sinfo_t_idle&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
&lt;br /&gt;
Submit your job:&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;sbatch testjob.sh&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
&lt;br /&gt;
When you queued a job, you can show its status:&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;squeue&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
If resources are not immediately available add &amp;lt;code&amp;gt;--start&amp;lt;/code&amp;gt; to show its expected start time:&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;squeue --start&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
If you want to cancel your job run&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;scancel &amp;lt;jobid&amp;gt;&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
&lt;br /&gt;
Show all of your jobs started on the current day or since the specified starttime.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;sacct --format=User,JobID,Jobname%50,partition,state,start,end,elapsed,time,MaxRss,MaxVMSize,nnodes,ncpus,nodelist  --starttime=2025-12-01&amp;lt;/syntaxhighlight&amp;gt;&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=NEMO2/Workspaces&amp;diff=15679</id>
		<title>NEMO2/Workspaces</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=NEMO2/Workspaces&amp;diff=15679"/>
		<updated>2026-01-12T15:47:20Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: add DACHS to ws_restore list&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&amp;lt;div style=&amp;quot;border: 3px solid #ffc107; padding: 15px; background-color: #fff3cd; margin: 10px 0;&amp;quot;&amp;gt;&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; This is the updated Workspaces guide. The old wiki: [[Workspace]].&lt;br /&gt;
&amp;lt;/div&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Workspace tools&#039;&#039;&#039; provide temporary storage spaces called &#039;&#039;&#039;workspaces&#039;&#039;&#039; for your calculations. They are meant for data that needs to persist longer than a single job, but not permanently.&lt;br /&gt;
&lt;br /&gt;
== What are Workspaces? ==&lt;br /&gt;
&lt;br /&gt;
Workspaces give you access to the cluster&#039;s fast parallel filesystems (like Lustre or Weka). &#039;&#039;&#039;You cannot write directly to these parallel filesystems&#039;&#039;&#039; - workspaces provide your designated area.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Use workspaces for:&#039;&#039;&#039;&lt;br /&gt;
* Jobs generating intermediate data&lt;br /&gt;
* Data shared between multiple compute nodes&lt;br /&gt;
* Multi-step workflows&lt;br /&gt;
* Temporary scratch space during calculations&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Don&#039;t use workspaces for:&#039;&#039;&#039;&lt;br /&gt;
* Permanent storage (use HOME or project directories)&lt;br /&gt;
* Single-node temporary files (use &amp;lt;tt&amp;gt;$TMPDIR&amp;lt;/tt&amp;gt; instead)&lt;br /&gt;
&lt;br /&gt;
== Important - Read First ==&lt;br /&gt;
&lt;br /&gt;
* &#039;&#039;&#039;No Backup:&#039;&#039;&#039; Data is &#039;&#039;&#039;not backed up&#039;&#039;&#039; and will be &#039;&#039;&#039;automatically deleted&#039;&#039;&#039; after expiration&lt;br /&gt;
* &#039;&#039;&#039;Time-limited:&#039;&#039;&#039; Lifetime typically 30-100 days (cluster-specific). See [[Workspaces/Advanced_Features/Quotas#Cluster-Specific_Workspace_Limits|Cluster Limits]]&lt;br /&gt;
* &#039;&#039;&#039;Automatic Reminders:&#039;&#039;&#039; Email notifications before expiration&lt;br /&gt;
* &#039;&#039;&#039;Backup Important Data:&#039;&#039;&#039; Copy results to permanent storage before expiration&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;For advanced features and detailed options:&#039;&#039;&#039; [[Workspaces/Advanced Features]]&lt;br /&gt;
&lt;br /&gt;
== Command Overview ==&lt;br /&gt;
&lt;br /&gt;
Main commands:&lt;br /&gt;
&lt;br /&gt;
* &amp;lt;tt&amp;gt;ws_allocate&amp;lt;/tt&amp;gt; - Create or extend workspace&lt;br /&gt;
* &amp;lt;tt&amp;gt;ws_list&amp;lt;/tt&amp;gt; - List your workspaces&lt;br /&gt;
* &amp;lt;tt&amp;gt;ws_find&amp;lt;/tt&amp;gt; - Find workspace path (for scripts)&lt;br /&gt;
* &amp;lt;tt&amp;gt;ws_extend&amp;lt;/tt&amp;gt; - Extend workspace lifetime&lt;br /&gt;
* &amp;lt;tt&amp;gt;ws_release&amp;lt;/tt&amp;gt; - Release (delete) workspace&lt;br /&gt;
* &amp;lt;tt&amp;gt;ws_restore&amp;lt;/tt&amp;gt; - Restore expired/released workspace&lt;br /&gt;
* &amp;lt;tt&amp;gt;ws_register&amp;lt;/tt&amp;gt; - Create symbolic links&lt;br /&gt;
&lt;br /&gt;
All commands support &amp;lt;tt&amp;gt;-h&amp;lt;/tt&amp;gt; for help.&lt;br /&gt;
&lt;br /&gt;
== Quick Start ==&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
|- &lt;br /&gt;
!style=&amp;quot;width:40%&amp;quot; | Task&lt;br /&gt;
!style=&amp;quot;width:60%&amp;quot; | Command&lt;br /&gt;
|-&lt;br /&gt;
|Create workspace (30 days)&lt;br /&gt;
|&amp;lt;tt&amp;gt;ws_allocate myWs 30&amp;lt;/tt&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
|Create group workspace&lt;br /&gt;
|&amp;lt;tt&amp;gt;ws_allocate -G groupname myWs 30&amp;lt;/tt&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
|List all workspaces&lt;br /&gt;
|&amp;lt;tt&amp;gt;ws_list&amp;lt;/tt&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
|See what expires soon&lt;br /&gt;
|&amp;lt;tt&amp;gt;ws_list -Rr&amp;lt;/tt&amp;gt; (&amp;lt;tt&amp;gt;-R&amp;lt;/tt&amp;gt;=by time, &amp;lt;tt&amp;gt;-r&amp;lt;/tt&amp;gt;=reverse)&lt;br /&gt;
|-&lt;br /&gt;
|Find path (for scripts)&lt;br /&gt;
|&amp;lt;tt&amp;gt;ws_find myWs&amp;lt;/tt&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
|Extend by 30 days&lt;br /&gt;
|&amp;lt;tt&amp;gt;ws_extend myWs 30&amp;lt;/tt&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
|Delete workspace&lt;br /&gt;
|&amp;lt;tt&amp;gt;ws_release myWs&amp;lt;/tt&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
|Restore workspace&lt;br /&gt;
|&amp;lt;tt&amp;gt;ws_restore -l&amp;lt;/tt&amp;gt; then &amp;lt;tt&amp;gt;ws_restore oldname newname&amp;lt;/tt&amp;gt;&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Create Workspace ==&lt;br /&gt;
&lt;br /&gt;
Create a workspace with a &#039;&#039;&#039;name&#039;&#039;&#039; and &#039;&#039;&#039;lifetime&#039;&#039;&#039; in days:&lt;br /&gt;
&lt;br /&gt;
   $ ws_allocate myWs 30                    # Create for 30 days&lt;br /&gt;
&lt;br /&gt;
Returns:&lt;br /&gt;
 &lt;br /&gt;
   Workspace created. Duration is 720 hours. &lt;br /&gt;
   Further extensions available: 3&lt;br /&gt;
   /work/workspace/scratch/username-myWs-0&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Common options:&#039;&#039;&#039;&lt;br /&gt;
&lt;br /&gt;
   $ ws_allocate -G groupname myWs 30       # Group-writable (for teams)&lt;br /&gt;
   $ ws_allocate -g myWs 30                 # Group-readable&lt;br /&gt;
   $ ws_allocate -F ffuc myWs 30            # bwUniCluster 3.0: Flash filesystem&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Capture path in variable:&#039;&#039;&#039;&lt;br /&gt;
&lt;br /&gt;
   $ WORKSPACE=$(ws_allocate myWs 30)&lt;br /&gt;
   $ cd &amp;quot;$WORKSPACE&amp;quot;&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Important:&#039;&#039;&#039; Running the same command again is safe - returns the existing workspace path.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Details:&#039;&#039;&#039; [[Workspaces/Advanced_Features/ws_allocate|Advanced Features guide]]&lt;br /&gt;
&lt;br /&gt;
== List Your Workspaces ==&lt;br /&gt;
&lt;br /&gt;
   $ ws_list                                # List all workspaces&lt;br /&gt;
&lt;br /&gt;
Shows workspace ID, location, extensions, creation date, and remaining time.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Common options:&#039;&#039;&#039;&lt;br /&gt;
&lt;br /&gt;
   $ ws_list -Rr                            # Sort by remaining time, reverse (last to expire first)&lt;br /&gt;
   $ ws_list -s                             # Short format (names only, for scripts)&lt;br /&gt;
   $ ws_list -g                             # Show group workspaces&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; To list expired workspaces for restore, use &amp;lt;tt&amp;gt;ws_restore -l&amp;lt;/tt&amp;gt;. See [[#Restore_Workspace|Restore]].&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Details:&#039;&#039;&#039; [[Workspaces/Advanced_Features/ws_list|Advanced Features guide]]&lt;br /&gt;
&lt;br /&gt;
== Extend Workspace Lifetime ==&lt;br /&gt;
&lt;br /&gt;
Extend before workspace expires:&lt;br /&gt;
&lt;br /&gt;
   $ ws_extend myWs 30                      # Extend by 30 days from now&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Alternative:&#039;&#039;&#039;&lt;br /&gt;
&lt;br /&gt;
   $ ws_allocate -x myWs 30                 # Same result&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; Each extension consumes one available extension. See [[Workspaces/Advanced_Features/Quotas#Cluster-Specific_Workspace_Limits|Cluster Limits]].&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Group workspaces:&#039;&#039;&#039; See [[#Extend_Group_Workspace|Extend Group Workspace]] for extending workspaces created by colleagues.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Details:&#039;&#039;&#039; [[Workspaces/Advanced_Features/ws_extend|Advanced Features guide]]&lt;br /&gt;
&lt;br /&gt;
== Release (Delete) Workspace ==&lt;br /&gt;
&lt;br /&gt;
When no longer needed:&lt;br /&gt;
&lt;br /&gt;
   $ ws_release myWs                        # Release workspace&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;What happens:&#039;&#039;&#039;&lt;br /&gt;
* Workspace becomes inaccessible immediately&lt;br /&gt;
* Data kept for short grace period (typically until next cleanup)&lt;br /&gt;
* Can be restored with &amp;lt;tt&amp;gt;ws_restore&amp;lt;/tt&amp;gt; during grace period&lt;br /&gt;
* May still count toward quota until final deletion&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Details:&#039;&#039;&#039; [[Workspaces/Advanced_Features/ws_release|Advanced Features guide]]&lt;br /&gt;
&lt;br /&gt;
== Restore Workspace ==&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
|- &lt;br /&gt;
!style=&amp;quot;width:40%&amp;quot; | Works on cluster&lt;br /&gt;
!style=&amp;quot;width:10%&amp;quot; | bwUC 3.0&lt;br /&gt;
!style=&amp;quot;width:10%&amp;quot; | BinAC2&lt;br /&gt;
!style=&amp;quot;width:10%&amp;quot; | Helix&lt;br /&gt;
!style=&amp;quot;width:10%&amp;quot; | JUSTUS 2&lt;br /&gt;
!style=&amp;quot;width:10%&amp;quot; | NEMO2&lt;br /&gt;
!style=&amp;quot;width:10%&amp;quot; | DACHS&lt;br /&gt;
|-&lt;br /&gt;
|&amp;lt;tt&amp;gt;ws_restore&amp;lt;/tt&amp;gt;&lt;br /&gt;
|style=&amp;quot;background-color:#90EE90; text-align:center;&amp;quot; | ✓&lt;br /&gt;
|style=&amp;quot;background-color:#90EE90; text-align:center;&amp;quot; | ✓&lt;br /&gt;
|style=&amp;quot;background-color:#90EE90; text-align:center;&amp;quot; | ✓&lt;br /&gt;
|style=&amp;quot;background-color:#90EE90; text-align:center;&amp;quot; | ✓&lt;br /&gt;
|style=&amp;quot;background-color:#90EE90; text-align:center;&amp;quot; | ✓&lt;br /&gt;
|style=&amp;quot;background-color:#90EE90; text-align:center;&amp;quot; | ✓&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Recover expired or released workspaces within grace period:&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Restore procedure:&#039;&#039;&#039;&lt;br /&gt;
&lt;br /&gt;
   $ ws_restore -l                          # (1) List restorable workspaces&lt;br /&gt;
   $ ws_allocate restored 60                # (2) Create target workspace&lt;br /&gt;
   $ ws_restore username-myWs-0 restored    # (3) Restore&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Important:&#039;&#039;&#039; Use the &#039;&#039;&#039;full name&#039;&#039;&#039; from &amp;lt;tt&amp;gt;ws_restore -l&amp;lt;/tt&amp;gt; (with username and timestamp), not the short name.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Details:&#039;&#039;&#039; [[Workspaces/Advanced_Features/ws_restore|Advanced Features guide]]&lt;br /&gt;
&lt;br /&gt;
== Work with Groups (Share Workspaces) ==&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
|- &lt;br /&gt;
!style=&amp;quot;width:40%&amp;quot; | Works on cluster&lt;br /&gt;
!style=&amp;quot;width:10%&amp;quot; | bwUC 3.0&lt;br /&gt;
!style=&amp;quot;width:10%&amp;quot; | BinAC2&lt;br /&gt;
!style=&amp;quot;width:10%&amp;quot; | Helix&lt;br /&gt;
!style=&amp;quot;width:10%&amp;quot; | JUSTUS 2&lt;br /&gt;
!style=&amp;quot;width:10%&amp;quot; | NEMO2&lt;br /&gt;
|-&lt;br /&gt;
|&amp;lt;tt&amp;gt;-g&amp;lt;/tt&amp;gt; (group-readable)&lt;br /&gt;
| style=&amp;quot;text-align:center;&amp;quot; | &lt;br /&gt;
| style=&amp;quot;text-align:center;&amp;quot; | &lt;br /&gt;
| style=&amp;quot;text-align:center;&amp;quot; | &lt;br /&gt;
| style=&amp;quot;text-align:center;&amp;quot; | &lt;br /&gt;
|style=&amp;quot;background-color:#90EE90; text-align:center;&amp;quot; | ✓&lt;br /&gt;
|-&lt;br /&gt;
|&amp;lt;tt&amp;gt;-G&amp;lt;/tt&amp;gt; (group-writable)&lt;br /&gt;
| style=&amp;quot;text-align:center;&amp;quot; | &lt;br /&gt;
| style=&amp;quot;text-align:center;&amp;quot; | &lt;br /&gt;
| style=&amp;quot;text-align:center;&amp;quot; | &lt;br /&gt;
| style=&amp;quot;text-align:center;&amp;quot; | &lt;br /&gt;
|style=&amp;quot;background-color:#90EE90; text-align:center;&amp;quot; | ✓&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Simple team collaboration with group workspaces:&lt;br /&gt;
&lt;br /&gt;
=== Create Group Workspace ===&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Group-readable (read-only):&#039;&#039;&#039;&lt;br /&gt;
&lt;br /&gt;
   $ ws_allocate -g myWs 30&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Group-writable (recommended):&#039;&#039;&#039;&lt;br /&gt;
&lt;br /&gt;
   $ ws_allocate -G projectgroup myWs 30    # Replace &#039;projectgroup&#039; with your group&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Tip:&#039;&#039;&#039; Set default in &amp;lt;tt&amp;gt;~/.ws_user.conf&amp;lt;/tt&amp;gt;:&lt;br /&gt;
&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
groupname: projectgroup&lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
Then simply: &amp;lt;tt&amp;gt;ws_allocate myWs 30&amp;lt;/tt&amp;gt;&lt;br /&gt;
&lt;br /&gt;
=== List Group Workspaces ===&lt;br /&gt;
&lt;br /&gt;
   $ ws_list -g                             # Show all group workspaces&lt;br /&gt;
&lt;br /&gt;
=== Extend Group Workspace ===&lt;br /&gt;
&lt;br /&gt;
Anyone in the group can extend group-writable workspaces (&amp;lt;tt&amp;gt;-G&amp;lt;/tt&amp;gt;):&lt;br /&gt;
&lt;br /&gt;
   $ ws_extend myWs 30                      # If you created it&lt;br /&gt;
   $ ws_allocate -x -u alice myWs 30        # If colleague created it&lt;br /&gt;
&lt;br /&gt;
=== Manage Reminders ===&lt;br /&gt;
&lt;br /&gt;
Take over reminder responsibility:&lt;br /&gt;
&lt;br /&gt;
   $ ws_allocate -r 7 -u alice -x myWs 0    # Update timing and take over reminders&lt;br /&gt;
&lt;br /&gt;
Changes reminder to 7 days before expiration and redirects emails to you.&lt;br /&gt;
&lt;br /&gt;
=== Why Use Group Workspaces? ===&lt;br /&gt;
&lt;br /&gt;
* Simple collaboration - everyone accesses same data&lt;br /&gt;
* No permission problems - automatic group permissions&lt;br /&gt;
* Independent extensions - team can extend without creator&lt;br /&gt;
* Easy discovery - &amp;lt;tt&amp;gt;ws_list -g&amp;lt;/tt&amp;gt; shows all team workspaces&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Advanced sharing:&#039;&#039;&#039; [[Workspaces/Advanced_Features/Sharing|Sharing guide]] for ACLs and ws_share&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Software&amp;diff=15516</id>
		<title>DACHS/Software</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Software&amp;diff=15516"/>
		<updated>2025-11-25T08:22:52Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;For available Software Modules, please [[DACHS/Login|login via SSH]] described above and type &amp;lt;code&amp;gt;module avail&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Halcon == &lt;br /&gt;
&lt;br /&gt;
Halcon 24.11 is available on DACHS for users of HS Esslingen.&lt;br /&gt;
&lt;br /&gt;
 module help cs/halcon/24.11&lt;br /&gt;
&lt;br /&gt;
TODO: configure license.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Software&amp;diff=15515</id>
		<title>DACHS/Software</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Software&amp;diff=15515"/>
		<updated>2025-11-25T08:20:11Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;For available Software Modules, please [[DACHS/Login|login via SSH]] described above and type &amp;lt;code&amp;gt;module avail&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Halcon == &lt;br /&gt;
&lt;br /&gt;
Halcon 24.11 is available on DACHS for users of HS Esslingen.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight&amp;gt;&lt;br /&gt;
module help cs/halcon/24.11&lt;br /&gt;
&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
&lt;br /&gt;
TODO: configure license.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Quickstart_Slurm&amp;diff=15514</id>
		<title>DACHS/Quickstart Slurm</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Quickstart_Slurm&amp;diff=15514"/>
		<updated>2025-11-25T08:06:24Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Typical SBATCH script */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&amp;lt;span id=&amp;quot;quickstart&amp;quot;&amp;gt;&amp;lt;/span&amp;gt;&lt;br /&gt;
= Quickstart =&lt;br /&gt;
&lt;br /&gt;
&amp;lt;span id=&amp;quot;contact-and-further-links-to-bwhpc-wiki&amp;quot;&amp;gt;&amp;lt;/span&amp;gt;&lt;br /&gt;
== Contact and Further Links to bwHPC wiki ==&lt;br /&gt;
&lt;br /&gt;
If you don&#039;t find the information you need in this wiki, you can always reach us at [mailto:dachs-admin@hs-esslingen.de dachs-admin@hs-esslingen.de].&lt;br /&gt;
&lt;br /&gt;
&amp;lt;span id=&amp;quot;typical-sbatch-script&amp;quot;&amp;gt;&amp;lt;/span&amp;gt;&lt;br /&gt;
== Typical SBATCH script ==&lt;br /&gt;
&lt;br /&gt;
This is just a brief guide to get you started. All queues, limits, and hardware are documented in detail at the [[DACHS/Hardware]].&lt;br /&gt;
&lt;br /&gt;
Our default queue is &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; that you specify with &amp;lt;code&amp;gt;--partition=gpu1&amp;lt;/code&amp;gt; explicitly. Other queues are &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt; (4 AMD MI300A APUs) and &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt; (8 NVIDIA H100 GPUs). For more deatiled information, visit [https://wiki.bwhpc.de/e/DACHS/Queues DACHS/Queues].&lt;br /&gt;
&lt;br /&gt;
This is the content of &amp;lt;code&amp;gt;testjob.sh&amp;lt;/code&amp;gt;. It is basically a Bash script with some instructions in the format of comment for the Slurm scheduler.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;#!/bin/bash&lt;br /&gt;
#SBATCH --ntasks=1               # allocate 1 CPU&lt;br /&gt;
#SBATCH --time=30:00             # time limit of 30 min&lt;br /&gt;
#SBATCH --mem=42gb               # allocate 42 GB RAM&lt;br /&gt;
#SBATch --gres=gpu:1             # allocate one GPU&lt;br /&gt;
#SBATCH --job-name=&amp;quot;CHANGEME JOBNAME&amp;quot;&lt;br /&gt;
# Uncomment the following lines to get email notifications about your job&lt;br /&gt;
# #SBATCH --mail-type=ALL        # list of &amp;quot;ALL,START,END&lt;br /&gt;
# #SBATCH --mail-user=CHANGME@EMAIL.COM&lt;br /&gt;
&lt;br /&gt;
# You Shell script that setups your job and starts your work is here.&lt;br /&gt;
# That might include loading a module from provided software (check with&lt;br /&gt;
# `module avail` or sourcing a Python environment.&lt;br /&gt;
&lt;br /&gt;
# Load Python 3.13.3 compiled with gnu 14.2&lt;br /&gt;
module load devel/python/3.13.3-gnu-14.2&lt;br /&gt;
&lt;br /&gt;
# Run your Python script that you previously prepared on the Login node.&lt;br /&gt;
uv run python3 main.py&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
For a detailed overview of slurm visit the [https://wiki.bwhpc.de/e/BwUniCluster2.0/Slurm SBATCH options and Slurm wiki page].&lt;br /&gt;
&lt;br /&gt;
You can display available nodes by running&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;sinfo_t_idle&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
&lt;br /&gt;
Submit your job:&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;sbatch testjob.sh&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
&lt;br /&gt;
When you queued a job, you can show its status:&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;squeue&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
If resources are not immediately available add &amp;lt;code&amp;gt;--start&amp;lt;/code&amp;gt; to show its expected start time:&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;squeue --start&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
If you want to cancel your job run&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;scancel &amp;lt;jobid&amp;gt;&amp;lt;/syntaxhighlight&amp;gt;&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15513</id>
		<title>DACHS/Jupyter</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Jupyter&amp;diff=15513"/>
		<updated>2025-11-25T07:58:53Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: Created page with &amp;quot;We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/].  == What is JupyterHub? ==  To quote JupyterHub from their [https://jupyter.org/hub website]:  &amp;lt;blockquote&amp;gt; JupyterHub: A multi-user version of the notebook designed for companies, classrooms and research labs  JupyterHub brings the power of notebooks to groups of users. It gives users access to computational environments and resources withou...&amp;quot;&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;We provide [https://jupyter.org/hub JupyterHub] at [https://dachs-jupyter.hs-esslingen.de https://dachs-jupyter.hs-esslingen.de/].&lt;br /&gt;
&lt;br /&gt;
== What is JupyterHub? ==&lt;br /&gt;
&lt;br /&gt;
To quote JupyterHub from their [https://jupyter.org/hub website]:&lt;br /&gt;
&lt;br /&gt;
&amp;lt;blockquote&amp;gt;&lt;br /&gt;
JupyterHub: A multi-user version of the notebook designed for companies, classrooms and research labs&lt;br /&gt;
&lt;br /&gt;
JupyterHub brings the power of notebooks to groups of users. It gives users access to computational environments and resources without burdening the users with installation and maintenance tasks. Users - including students, researchers, and data scientists - can get their work done in their own workspaces on shared resources which can be managed efficiently by system administrators.&lt;br /&gt;
&amp;lt;/blockquote&amp;gt;&lt;br /&gt;
&lt;br /&gt;
It&#039;s a simpler way to access the resources of DACHS by using your browser.&lt;br /&gt;
&lt;br /&gt;
== Prerequisites ==&lt;br /&gt;
&lt;br /&gt;
# You must be &#039;&#039;&#039;able to [[DACHS/Login|login to DACHS]] via SSH and must have done so at least once&#039;&#039;&#039;. This ensures that your home directory is setup properly on DACHS.&lt;br /&gt;
# Make sure you&#039;re &#039;&#039;&#039;connected to the VPN of your university&#039;&#039;&#039;. Access to our JupyterHub instance is only allowed from within the BelWue network.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15512</id>
		<title>DACHS</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15512"/>
		<updated>2025-11-25T07:42:51Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{| style=&amp;quot;width: 100%; border-spacing: 5px;&amp;quot;&lt;br /&gt;
| style=&amp;quot;text-align:center; color:#000;vertical-align:middle;font-size:75%;&amp;quot; |&lt;br /&gt;
[[File:DACHS_Logo.png|center|border|250px||]] &lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) supports data scientists, machine learning experts and in general engineers for research and education, specifically teaching of the participating Universities of Applied Science.&lt;br /&gt;
&lt;br /&gt;
You can always reach us via Email at [mailto:dachs-admin@hs-esslingen.de dachs-admin@hs-esslingen.de].&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;  background:#eeeefe; width:100%;&amp;quot; &lt;br /&gt;
| style=&amp;quot;padding:8px; background:#dedefe; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Training &amp;amp; Support&lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
* [[DACHS/Getting_Started|Getting Started]]&lt;br /&gt;
&amp;lt;!-- * [http://dachs.hs-esslingen.de/ Cluster Status and Usage] --&amp;gt;&lt;br /&gt;
* [https://training.bwhpc.de E-Learning Courses]&lt;br /&gt;
* [[DACHS/Support|Contact and Support]]&lt;br /&gt;
* Send [[:Category:Feedback|Feedback]] about Wiki pages&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#cef2e0; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | User Documentation&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* [[DACHS/Registration|Registration]]&lt;br /&gt;
* [[DACHS/Login|Login to DACHS via SSH]]&lt;br /&gt;
* [[DACHS/Hardware|Hardware and Architecture]]&lt;br /&gt;
* [[DACHS/Quickstart Slurm|Quickstart &amp;amp;mdash; Submit Jobs]]&lt;br /&gt;
* How to use provided [[DACHS/Software|Software]] on DACHS&lt;br /&gt;
* Running Jobs&lt;br /&gt;
** [[DACHS/Queues|Overview of Queues (partitions) on DACHS]]&lt;br /&gt;
** [[BwUniCluster2.0/Slurm|Slurm Queuing System]] (page of bwUniCluster2.0 &amp;amp;mdash; applies to DACHS as well)&lt;br /&gt;
** [[DACHS/Jupyter|Interactive Computing with Jupyter]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
{| style=&amp;quot;  background:#e6e9eb; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#d1dadf; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Cluster Funding&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* Please [[DACHS/Acknowledgement|acknowledge]] the cluster in your publications.&lt;br /&gt;
|}&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15511</id>
		<title>DACHS</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15511"/>
		<updated>2025-11-25T07:42:08Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{| style=&amp;quot;width: 100%; border-spacing: 5px;&amp;quot;&lt;br /&gt;
| style=&amp;quot;text-align:center; color:#000;vertical-align:middle;font-size:75%;&amp;quot; |&lt;br /&gt;
[[File:DACHS_Logo.png|center|border|250px||]] &lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) supports data scientists, machine learning experts and in general engineers for research and education, specifically teaching of the participating Universities of Applied Science.&lt;br /&gt;
&lt;br /&gt;
You can always reach us via Email at [mailto:dachs-admin@hs-esslingen.de dachs-admin@hs-esslingen.de].&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;  background:#eeeefe; width:100%;&amp;quot; &lt;br /&gt;
| style=&amp;quot;padding:8px; background:#dedefe; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Training &amp;amp; Support&lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
* [[DACHS/Getting_Started|Getting Started]]&lt;br /&gt;
&amp;lt;!-- * [http://dachs.hs-esslingen.de/ Cluster Status and Usage] --&amp;gt;&lt;br /&gt;
* [https://training.bwhpc.de E-Learning Courses]&lt;br /&gt;
* [[DACHS/Support|Contact and Support]]&lt;br /&gt;
* Send [[:Category:Feedback|Feedback]] about Wiki pages&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#cef2e0; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | User Documentation&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* [[DACHS/Registration|Registration]]&lt;br /&gt;
* [[DACHS/Login|Login to DACHS via SSH]]&lt;br /&gt;
* [[DACHS/Hardware|Hardware and Architecture]]&lt;br /&gt;
* [[DACHS/Quickstart Slurm|Quickstart &amp;amp;mdash; Submit Jobs]]&lt;br /&gt;
* How to use provided [[DACHS/Software|Software]] on DACHS&lt;br /&gt;
* Running Jobs&lt;br /&gt;
** [[DACHS/Queues|Overview of Queues (parition) on DACHS]]&lt;br /&gt;
** [[BwUniCluster2.0/Slurm|Slurm Queuing System]] (page of bwUniCluster2.0 &amp;amp;mdash; applies to DACHS as well)&lt;br /&gt;
** [[DACHS/Jupyter|Interactive Computing with Jupyter]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
{| style=&amp;quot;  background:#e6e9eb; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#d1dadf; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Cluster Funding&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* Please [[DACHS/Acknowledgement|acknowledge]] the cluster in your publications.&lt;br /&gt;
|}&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Queues&amp;diff=15510</id>
		<title>DACHS/Queues</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Queues&amp;diff=15510"/>
		<updated>2025-11-25T07:37:13Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Multiple nodes */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;__TOC__&lt;br /&gt;
&lt;br /&gt;
== Partitions ==&lt;br /&gt;
DACHS offers three partitions in Slurm, which map directly to the node types: &lt;br /&gt;
&lt;br /&gt;
* 45 nodes with one NVIDIA L40S GPU&lt;br /&gt;
* one node with 4 AMD MI300A APUs&lt;br /&gt;
* one node with 8 NVIDIA H100 GPUs&lt;br /&gt;
&lt;br /&gt;
== sinfo_t_idle ==&lt;br /&gt;
To see the available nodes, DACHS offers the tool &#039;&#039;sinfo_t_info&#039;&#039;, which any user may call.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;&lt;br /&gt;
$ sinfo_t_idle&lt;br /&gt;
Partition gpu1*         :      7 nodes idle&lt;br /&gt;
Partition gpu4          :      1 nodes idle&lt;br /&gt;
Partition gpu8          :      0 nodes idle&lt;br /&gt;
&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== sbatch -p &#039;&#039;partition&#039;&#039; ==&lt;br /&gt;
Batch jobs specify compute requirements, which must fit the resources as in maximum (wall-)time, memory and GPU resources.&lt;br /&gt;
If You require a GPU, You must specify this with your request.&lt;br /&gt;
These are restricted and must fit the available &#039;&#039;&#039;partitions&#039;&#039;&#039;.&lt;br /&gt;
Since requested compute resources are NOT always automatically mapped to the correct queue class, &#039;&#039;&#039;you must add the correct queue class to your sbatch command &#039;&#039;&#039;.&lt;br /&gt;
&amp;lt;font color=red&amp;gt;As with bwUniCluster, the specification of a partition is required.&amp;lt;/font&amp;gt; &lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
Details are:&lt;br /&gt;
&lt;br /&gt;
{| width=750px class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! colspan=&amp;quot;5&amp;quot; | DACHS &amp;lt;br&amp;gt; sbatch -p &#039;&#039;partition&#039;&#039;&lt;br /&gt;
|- style=&amp;quot;text-align:left;&amp;quot;&lt;br /&gt;
! partition !! node !! default resources !! maximum resources&lt;br /&gt;
|- style=&amp;quot;text-align:left&amp;quot;&lt;br /&gt;
| gpu1&lt;br /&gt;
| gpu1[01-45]&lt;br /&gt;
| time=30, mem-per-node=5000mb&lt;br /&gt;
| time=72:00:00, nodes=16, mem-per-node=300000mb, res=gpu:1&lt;br /&gt;
|- style=&amp;quot;text-align:left;&amp;quot;&lt;br /&gt;
| gpu4&lt;br /&gt;
| gpu401&lt;br /&gt;
| time=30, mem-per-cpu=5000mb&lt;br /&gt;
| time=72:00:00, nodes=1, mem=500000mb, ntasks-per-node=96&lt;br /&gt;
|- style=&amp;quot;vertical-align:top; text-align:left&amp;quot;&lt;br /&gt;
| gpu8&lt;br /&gt;
| gpu801&lt;br /&gt;
| time=30, mem-per-cpu=5000mb, cpus-per-gpu=8&lt;br /&gt;
| time=48:00:00, mem=752000mb, ntasks-per-node=96&lt;br /&gt;
|- &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Default resources of a queue class defines time, #tasks and memory if not explicitly given with sbatch command. Resource list acronyms &amp;lt;code&amp;gt;--time&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--ntasks&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--nodes&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--mem&amp;lt;/code&amp;gt; and &amp;lt;code&amp;gt;--mem-per-cpu&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
A typical Slurm batch script (called for brevity &amp;lt;code&amp;gt;python_run.slurm&amp;lt;/code&amp;gt;) for 1-node requiring one NVIDIA L40S GPU:&lt;br /&gt;
 #!/bin/bash&lt;br /&gt;
 #SBATCH --partition=gpu1&lt;br /&gt;
 #SBATCH --ntasks-per-gpu=48&lt;br /&gt;
 #SBATCH --gres=gpu:1&lt;br /&gt;
 #SBATCH --time=1:00:00&lt;br /&gt;
 #SBATCH --mail-type=all&lt;br /&gt;
 #SBATCH --mail-user=my_email@hs-esslingen.de&lt;br /&gt;
 module load devel/cuda/12.4&lt;br /&gt;
 cd $TMPDIR&lt;br /&gt;
 python3 -m venv my_environment&lt;br /&gt;
 . my_environment/bin/activate&lt;br /&gt;
 python3 -m pip install -r $HOME/my_requirements.txt&lt;br /&gt;
 rsync -avz $HOME/my_data_dir/ .&lt;br /&gt;
 time python3 $HOME/python_script.py&lt;br /&gt;
&lt;br /&gt;
Submitting &amp;lt;code&amp;gt;sbatch python_run.slurm&amp;lt;/code&amp;gt; will allocate one compute node and allocate the one available GPU for 1 hour. Furthermore, this will load the CUDA module version 12.4. It will then change to the &#039;&#039;&#039;fast&#039;&#039;&#039; scratch directory specified in the environment variable &amp;lt;code&amp;gt;TMPDIR&amp;lt;/code&amp;gt;.&lt;br /&gt;
You &#039;&#039;&#039;have&#039;&#039;&#039; to allocate the GPU, otherwise You may not use it.&lt;br /&gt;
It will then follow Python&#039;s best practices and create a new Virtual Environment in that directory, then installing the dependencies of the projects detailed in &amp;lt;code&amp;gt;my_requirements.txt&amp;lt;/code&amp;gt;&lt;br /&gt;
It then copies the data directory in &amp;lt;code&amp;gt;my_data_dir&amp;lt;/code&amp;gt; to this directory using &amp;lt;code&amp;gt;rsync&amp;lt;/code&amp;gt;.&lt;br /&gt;
Finally, it executes your main python script, using the time command to figure out, how much time actually was used.&lt;br /&gt;
Alternatively you may time all the commands to get an estimate for Your next batch job.&lt;br /&gt;
&lt;br /&gt;
Here, Slurm will email to the specified address upon start and completion of the job with a summary.&lt;br /&gt;
&lt;br /&gt;
The &#039;&#039;&#039;better&#039;&#039;&#039; your approximation, the better the Slurm scheduler may allocate resources to all users.&lt;br /&gt;
&lt;br /&gt;
== Interactive usage ==&lt;br /&gt;
To &#039;&#039;&#039;get a good estimation&#039;&#039;&#039; of runtime, You may first want to try the resource &#039;&#039;interactively&#039;&#039;:&lt;br /&gt;
  &lt;br /&gt;
 srun --partition=gpu1 --ntasks-per-gpu=48 --gres=gpu:1 --pty /bin/bash&lt;br /&gt;
&lt;br /&gt;
Then You may execute the steps in &amp;lt;code&amp;gt;python_run.slurm&amp;lt;/code&amp;gt; script interactively, noting differences and amend your Slurm batch script.&lt;br /&gt;
&#039;&#039;Please note&#039;&#039; the &amp;lt;code&amp;gt;--pty&amp;lt;/code&amp;gt; which forwards the standard output and takes standard input to allow working with the Shell.&lt;br /&gt;
&lt;br /&gt;
== Multiple nodes ==&lt;br /&gt;
Of course You may allocate multiple GPUs across nodes running:&lt;br /&gt;
&lt;br /&gt;
 sbatch --nodes 4 ./python_run.slurm&lt;br /&gt;
&lt;br /&gt;
Please be aware, that TMPDIR is still local. For the time being run from Your $HOME or better yet from an allocated [[Workspace]].&lt;br /&gt;
&lt;br /&gt;
== Nodes with multiple GPUs == &lt;br /&gt;
The partitions &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt; and &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt; feature multiple GPUs.&lt;br /&gt;
The &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt; partition contains the node &amp;lt;code&amp;gt;gpu401&amp;lt;/code&amp;gt; featuring 4x AMD MI300A APUs each with 128GB of fast HMB3e memory shared between the 24 cores and the GPU.&lt;br /&gt;
You may use AMD&#039;s ROCm employing HIP, OpenACC or OpenCL to parallelize for the GPU. Please refer to the documentation on this node.&lt;br /&gt;
&lt;br /&gt;
The &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt; partition contains the node &amp;lt;code&amp;gt;gpu801&amp;lt;/code&amp;gt; featuring 8x NVIDIA H100 offering 80GB of VRAM each, interconnected using SXM5.&lt;br /&gt;
Please refer to the documentation on this node.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Queues&amp;diff=15509</id>
		<title>DACHS/Queues</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Queues&amp;diff=15509"/>
		<updated>2025-11-25T07:37:00Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Interactive usage */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;__TOC__&lt;br /&gt;
&lt;br /&gt;
== Partitions ==&lt;br /&gt;
DACHS offers three partitions in Slurm, which map directly to the node types: &lt;br /&gt;
&lt;br /&gt;
* 45 nodes with one NVIDIA L40S GPU&lt;br /&gt;
* one node with 4 AMD MI300A APUs&lt;br /&gt;
* one node with 8 NVIDIA H100 GPUs&lt;br /&gt;
&lt;br /&gt;
== sinfo_t_idle ==&lt;br /&gt;
To see the available nodes, DACHS offers the tool &#039;&#039;sinfo_t_info&#039;&#039;, which any user may call.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;&lt;br /&gt;
$ sinfo_t_idle&lt;br /&gt;
Partition gpu1*         :      7 nodes idle&lt;br /&gt;
Partition gpu4          :      1 nodes idle&lt;br /&gt;
Partition gpu8          :      0 nodes idle&lt;br /&gt;
&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== sbatch -p &#039;&#039;partition&#039;&#039; ==&lt;br /&gt;
Batch jobs specify compute requirements, which must fit the resources as in maximum (wall-)time, memory and GPU resources.&lt;br /&gt;
If You require a GPU, You must specify this with your request.&lt;br /&gt;
These are restricted and must fit the available &#039;&#039;&#039;partitions&#039;&#039;&#039;.&lt;br /&gt;
Since requested compute resources are NOT always automatically mapped to the correct queue class, &#039;&#039;&#039;you must add the correct queue class to your sbatch command &#039;&#039;&#039;.&lt;br /&gt;
&amp;lt;font color=red&amp;gt;As with bwUniCluster, the specification of a partition is required.&amp;lt;/font&amp;gt; &lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
Details are:&lt;br /&gt;
&lt;br /&gt;
{| width=750px class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! colspan=&amp;quot;5&amp;quot; | DACHS &amp;lt;br&amp;gt; sbatch -p &#039;&#039;partition&#039;&#039;&lt;br /&gt;
|- style=&amp;quot;text-align:left;&amp;quot;&lt;br /&gt;
! partition !! node !! default resources !! maximum resources&lt;br /&gt;
|- style=&amp;quot;text-align:left&amp;quot;&lt;br /&gt;
| gpu1&lt;br /&gt;
| gpu1[01-45]&lt;br /&gt;
| time=30, mem-per-node=5000mb&lt;br /&gt;
| time=72:00:00, nodes=16, mem-per-node=300000mb, res=gpu:1&lt;br /&gt;
|- style=&amp;quot;text-align:left;&amp;quot;&lt;br /&gt;
| gpu4&lt;br /&gt;
| gpu401&lt;br /&gt;
| time=30, mem-per-cpu=5000mb&lt;br /&gt;
| time=72:00:00, nodes=1, mem=500000mb, ntasks-per-node=96&lt;br /&gt;
|- style=&amp;quot;vertical-align:top; text-align:left&amp;quot;&lt;br /&gt;
| gpu8&lt;br /&gt;
| gpu801&lt;br /&gt;
| time=30, mem-per-cpu=5000mb, cpus-per-gpu=8&lt;br /&gt;
| time=48:00:00, mem=752000mb, ntasks-per-node=96&lt;br /&gt;
|- &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Default resources of a queue class defines time, #tasks and memory if not explicitly given with sbatch command. Resource list acronyms &amp;lt;code&amp;gt;--time&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--ntasks&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--nodes&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--mem&amp;lt;/code&amp;gt; and &amp;lt;code&amp;gt;--mem-per-cpu&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
A typical Slurm batch script (called for brevity &amp;lt;code&amp;gt;python_run.slurm&amp;lt;/code&amp;gt;) for 1-node requiring one NVIDIA L40S GPU:&lt;br /&gt;
 #!/bin/bash&lt;br /&gt;
 #SBATCH --partition=gpu1&lt;br /&gt;
 #SBATCH --ntasks-per-gpu=48&lt;br /&gt;
 #SBATCH --gres=gpu:1&lt;br /&gt;
 #SBATCH --time=1:00:00&lt;br /&gt;
 #SBATCH --mail-type=all&lt;br /&gt;
 #SBATCH --mail-user=my_email@hs-esslingen.de&lt;br /&gt;
 module load devel/cuda/12.4&lt;br /&gt;
 cd $TMPDIR&lt;br /&gt;
 python3 -m venv my_environment&lt;br /&gt;
 . my_environment/bin/activate&lt;br /&gt;
 python3 -m pip install -r $HOME/my_requirements.txt&lt;br /&gt;
 rsync -avz $HOME/my_data_dir/ .&lt;br /&gt;
 time python3 $HOME/python_script.py&lt;br /&gt;
&lt;br /&gt;
Submitting &amp;lt;code&amp;gt;sbatch python_run.slurm&amp;lt;/code&amp;gt; will allocate one compute node and allocate the one available GPU for 1 hour. Furthermore, this will load the CUDA module version 12.4. It will then change to the &#039;&#039;&#039;fast&#039;&#039;&#039; scratch directory specified in the environment variable &amp;lt;code&amp;gt;TMPDIR&amp;lt;/code&amp;gt;.&lt;br /&gt;
You &#039;&#039;&#039;have&#039;&#039;&#039; to allocate the GPU, otherwise You may not use it.&lt;br /&gt;
It will then follow Python&#039;s best practices and create a new Virtual Environment in that directory, then installing the dependencies of the projects detailed in &amp;lt;code&amp;gt;my_requirements.txt&amp;lt;/code&amp;gt;&lt;br /&gt;
It then copies the data directory in &amp;lt;code&amp;gt;my_data_dir&amp;lt;/code&amp;gt; to this directory using &amp;lt;code&amp;gt;rsync&amp;lt;/code&amp;gt;.&lt;br /&gt;
Finally, it executes your main python script, using the time command to figure out, how much time actually was used.&lt;br /&gt;
Alternatively you may time all the commands to get an estimate for Your next batch job.&lt;br /&gt;
&lt;br /&gt;
Here, Slurm will email to the specified address upon start and completion of the job with a summary.&lt;br /&gt;
&lt;br /&gt;
The &#039;&#039;&#039;better&#039;&#039;&#039; your approximation, the better the Slurm scheduler may allocate resources to all users.&lt;br /&gt;
&lt;br /&gt;
== Interactive usage ==&lt;br /&gt;
To &#039;&#039;&#039;get a good estimation&#039;&#039;&#039; of runtime, You may first want to try the resource &#039;&#039;interactively&#039;&#039;:&lt;br /&gt;
  &lt;br /&gt;
 srun --partition=gpu1 --ntasks-per-gpu=48 --gres=gpu:1 --pty /bin/bash&lt;br /&gt;
&lt;br /&gt;
Then You may execute the steps in &amp;lt;code&amp;gt;python_run.slurm&amp;lt;/code&amp;gt; script interactively, noting differences and amend your Slurm batch script.&lt;br /&gt;
&#039;&#039;Please note&#039;&#039; the &amp;lt;code&amp;gt;--pty&amp;lt;/code&amp;gt; which forwards the standard output and takes standard input to allow working with the Shell.&lt;br /&gt;
&lt;br /&gt;
== Multiple nodes ==&lt;br /&gt;
Of course You may allocate multiple GPUs across nodes running:&lt;br /&gt;
    sbatch --nodes 4 ./python_run.slurm&lt;br /&gt;
Please be aware, that TMPDIR is still local. For the time being run from Your $HOME or better yet from an allocated [[Workspace]].&lt;br /&gt;
&lt;br /&gt;
== Nodes with multiple GPUs == &lt;br /&gt;
The partitions &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt; and &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt; feature multiple GPUs.&lt;br /&gt;
The &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt; partition contains the node &amp;lt;code&amp;gt;gpu401&amp;lt;/code&amp;gt; featuring 4x AMD MI300A APUs each with 128GB of fast HMB3e memory shared between the 24 cores and the GPU.&lt;br /&gt;
You may use AMD&#039;s ROCm employing HIP, OpenACC or OpenCL to parallelize for the GPU. Please refer to the documentation on this node.&lt;br /&gt;
&lt;br /&gt;
The &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt; partition contains the node &amp;lt;code&amp;gt;gpu801&amp;lt;/code&amp;gt; featuring 8x NVIDIA H100 offering 80GB of VRAM each, interconnected using SXM5.&lt;br /&gt;
Please refer to the documentation on this node.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Queues&amp;diff=15508</id>
		<title>DACHS/Queues</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Queues&amp;diff=15508"/>
		<updated>2025-11-25T07:36:25Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* sinfo_t_idle */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;__TOC__&lt;br /&gt;
&lt;br /&gt;
== Partitions ==&lt;br /&gt;
DACHS offers three partitions in Slurm, which map directly to the node types: &lt;br /&gt;
&lt;br /&gt;
* 45 nodes with one NVIDIA L40S GPU&lt;br /&gt;
* one node with 4 AMD MI300A APUs&lt;br /&gt;
* one node with 8 NVIDIA H100 GPUs&lt;br /&gt;
&lt;br /&gt;
== sinfo_t_idle ==&lt;br /&gt;
To see the available nodes, DACHS offers the tool &#039;&#039;sinfo_t_info&#039;&#039;, which any user may call.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;&lt;br /&gt;
$ sinfo_t_idle&lt;br /&gt;
Partition gpu1*         :      7 nodes idle&lt;br /&gt;
Partition gpu4          :      1 nodes idle&lt;br /&gt;
Partition gpu8          :      0 nodes idle&lt;br /&gt;
&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== sbatch -p &#039;&#039;partition&#039;&#039; ==&lt;br /&gt;
Batch jobs specify compute requirements, which must fit the resources as in maximum (wall-)time, memory and GPU resources.&lt;br /&gt;
If You require a GPU, You must specify this with your request.&lt;br /&gt;
These are restricted and must fit the available &#039;&#039;&#039;partitions&#039;&#039;&#039;.&lt;br /&gt;
Since requested compute resources are NOT always automatically mapped to the correct queue class, &#039;&#039;&#039;you must add the correct queue class to your sbatch command &#039;&#039;&#039;.&lt;br /&gt;
&amp;lt;font color=red&amp;gt;As with bwUniCluster, the specification of a partition is required.&amp;lt;/font&amp;gt; &lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
Details are:&lt;br /&gt;
&lt;br /&gt;
{| width=750px class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! colspan=&amp;quot;5&amp;quot; | DACHS &amp;lt;br&amp;gt; sbatch -p &#039;&#039;partition&#039;&#039;&lt;br /&gt;
|- style=&amp;quot;text-align:left;&amp;quot;&lt;br /&gt;
! partition !! node !! default resources !! maximum resources&lt;br /&gt;
|- style=&amp;quot;text-align:left&amp;quot;&lt;br /&gt;
| gpu1&lt;br /&gt;
| gpu1[01-45]&lt;br /&gt;
| time=30, mem-per-node=5000mb&lt;br /&gt;
| time=72:00:00, nodes=16, mem-per-node=300000mb, res=gpu:1&lt;br /&gt;
|- style=&amp;quot;text-align:left;&amp;quot;&lt;br /&gt;
| gpu4&lt;br /&gt;
| gpu401&lt;br /&gt;
| time=30, mem-per-cpu=5000mb&lt;br /&gt;
| time=72:00:00, nodes=1, mem=500000mb, ntasks-per-node=96&lt;br /&gt;
|- style=&amp;quot;vertical-align:top; text-align:left&amp;quot;&lt;br /&gt;
| gpu8&lt;br /&gt;
| gpu801&lt;br /&gt;
| time=30, mem-per-cpu=5000mb, cpus-per-gpu=8&lt;br /&gt;
| time=48:00:00, mem=752000mb, ntasks-per-node=96&lt;br /&gt;
|- &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Default resources of a queue class defines time, #tasks and memory if not explicitly given with sbatch command. Resource list acronyms &amp;lt;code&amp;gt;--time&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--ntasks&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--nodes&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--mem&amp;lt;/code&amp;gt; and &amp;lt;code&amp;gt;--mem-per-cpu&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
A typical Slurm batch script (called for brevity &amp;lt;code&amp;gt;python_run.slurm&amp;lt;/code&amp;gt;) for 1-node requiring one NVIDIA L40S GPU:&lt;br /&gt;
 #!/bin/bash&lt;br /&gt;
 #SBATCH --partition=gpu1&lt;br /&gt;
 #SBATCH --ntasks-per-gpu=48&lt;br /&gt;
 #SBATCH --gres=gpu:1&lt;br /&gt;
 #SBATCH --time=1:00:00&lt;br /&gt;
 #SBATCH --mail-type=all&lt;br /&gt;
 #SBATCH --mail-user=my_email@hs-esslingen.de&lt;br /&gt;
 module load devel/cuda/12.4&lt;br /&gt;
 cd $TMPDIR&lt;br /&gt;
 python3 -m venv my_environment&lt;br /&gt;
 . my_environment/bin/activate&lt;br /&gt;
 python3 -m pip install -r $HOME/my_requirements.txt&lt;br /&gt;
 rsync -avz $HOME/my_data_dir/ .&lt;br /&gt;
 time python3 $HOME/python_script.py&lt;br /&gt;
&lt;br /&gt;
Submitting &amp;lt;code&amp;gt;sbatch python_run.slurm&amp;lt;/code&amp;gt; will allocate one compute node and allocate the one available GPU for 1 hour. Furthermore, this will load the CUDA module version 12.4. It will then change to the &#039;&#039;&#039;fast&#039;&#039;&#039; scratch directory specified in the environment variable &amp;lt;code&amp;gt;TMPDIR&amp;lt;/code&amp;gt;.&lt;br /&gt;
You &#039;&#039;&#039;have&#039;&#039;&#039; to allocate the GPU, otherwise You may not use it.&lt;br /&gt;
It will then follow Python&#039;s best practices and create a new Virtual Environment in that directory, then installing the dependencies of the projects detailed in &amp;lt;code&amp;gt;my_requirements.txt&amp;lt;/code&amp;gt;&lt;br /&gt;
It then copies the data directory in &amp;lt;code&amp;gt;my_data_dir&amp;lt;/code&amp;gt; to this directory using &amp;lt;code&amp;gt;rsync&amp;lt;/code&amp;gt;.&lt;br /&gt;
Finally, it executes your main python script, using the time command to figure out, how much time actually was used.&lt;br /&gt;
Alternatively you may time all the commands to get an estimate for Your next batch job.&lt;br /&gt;
&lt;br /&gt;
Here, Slurm will email to the specified address upon start and completion of the job with a summary.&lt;br /&gt;
&lt;br /&gt;
The &#039;&#039;&#039;better&#039;&#039;&#039; your approximation, the better the Slurm scheduler may allocate resources to all users.&lt;br /&gt;
&lt;br /&gt;
== Interactive usage ==&lt;br /&gt;
To &#039;&#039;&#039;get a good estimation&#039;&#039;&#039; of runtime, You may first want to try the resource &#039;&#039;interactively&#039;&#039;:&lt;br /&gt;
    srun --partition=gpu1 --ntasks-per-gpu=48 --gres=gpu:1 --pty /bin/bash&lt;br /&gt;
&lt;br /&gt;
Then You may execute the steps in &amp;lt;code&amp;gt;python_run.slurm&amp;lt;/code&amp;gt; script interactively, noting differences and amend your Slurm batch script.&lt;br /&gt;
&#039;&#039;Please note&#039;&#039; the &amp;lt;code&amp;gt;--pty&amp;lt;/code&amp;gt; which forwards the standard output and takes standard input to allow working with the Shell.&lt;br /&gt;
&lt;br /&gt;
== Multiple nodes ==&lt;br /&gt;
Of course You may allocate multiple GPUs across nodes running:&lt;br /&gt;
    sbatch --nodes 4 ./python_run.slurm&lt;br /&gt;
Please be aware, that TMPDIR is still local. For the time being run from Your $HOME or better yet from an allocated [[Workspace]].&lt;br /&gt;
&lt;br /&gt;
== Nodes with multiple GPUs == &lt;br /&gt;
The partitions &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt; and &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt; feature multiple GPUs.&lt;br /&gt;
The &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt; partition contains the node &amp;lt;code&amp;gt;gpu401&amp;lt;/code&amp;gt; featuring 4x AMD MI300A APUs each with 128GB of fast HMB3e memory shared between the 24 cores and the GPU.&lt;br /&gt;
You may use AMD&#039;s ROCm employing HIP, OpenACC or OpenCL to parallelize for the GPU. Please refer to the documentation on this node.&lt;br /&gt;
&lt;br /&gt;
The &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt; partition contains the node &amp;lt;code&amp;gt;gpu801&amp;lt;/code&amp;gt; featuring 8x NVIDIA H100 offering 80GB of VRAM each, interconnected using SXM5.&lt;br /&gt;
Please refer to the documentation on this node.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Queues&amp;diff=15507</id>
		<title>DACHS/Queues</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Queues&amp;diff=15507"/>
		<updated>2025-11-25T07:34:25Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Partitions */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;__TOC__&lt;br /&gt;
&lt;br /&gt;
== Partitions ==&lt;br /&gt;
DACHS offers three partitions in Slurm, which map directly to the node types: &lt;br /&gt;
&lt;br /&gt;
* 45 nodes with one NVIDIA L40S GPU&lt;br /&gt;
* one node with 4 AMD MI300A APUs&lt;br /&gt;
* one node with 8 NVIDIA H100 GPUs&lt;br /&gt;
&lt;br /&gt;
== sinfo_t_idle ==&lt;br /&gt;
To see the available nodes, DACHS offers the tool &#039;&#039;sinfo_t_info&#039;&#039;, which any user may call.&lt;br /&gt;
&lt;br /&gt;
== sbatch -p &#039;&#039;partition&#039;&#039; ==&lt;br /&gt;
Batch jobs specify compute requirements, which must fit the resources as in maximum (wall-)time, memory and GPU resources.&lt;br /&gt;
If You require a GPU, You must specify this with your request.&lt;br /&gt;
These are restricted and must fit the available &#039;&#039;&#039;partitions&#039;&#039;&#039;.&lt;br /&gt;
Since requested compute resources are NOT always automatically mapped to the correct queue class, &#039;&#039;&#039;you must add the correct queue class to your sbatch command &#039;&#039;&#039;.&lt;br /&gt;
&amp;lt;font color=red&amp;gt;As with bwUniCluster, the specification of a partition is required.&amp;lt;/font&amp;gt; &lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
Details are:&lt;br /&gt;
&lt;br /&gt;
{| width=750px class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! colspan=&amp;quot;5&amp;quot; | DACHS &amp;lt;br&amp;gt; sbatch -p &#039;&#039;partition&#039;&#039;&lt;br /&gt;
|- style=&amp;quot;text-align:left;&amp;quot;&lt;br /&gt;
! partition !! node !! default resources !! maximum resources&lt;br /&gt;
|- style=&amp;quot;text-align:left&amp;quot;&lt;br /&gt;
| gpu1&lt;br /&gt;
| gpu1[01-45]&lt;br /&gt;
| time=30, mem-per-node=5000mb&lt;br /&gt;
| time=72:00:00, nodes=16, mem-per-node=300000mb, res=gpu:1&lt;br /&gt;
|- style=&amp;quot;text-align:left;&amp;quot;&lt;br /&gt;
| gpu4&lt;br /&gt;
| gpu401&lt;br /&gt;
| time=30, mem-per-cpu=5000mb&lt;br /&gt;
| time=72:00:00, nodes=1, mem=500000mb, ntasks-per-node=96&lt;br /&gt;
|- style=&amp;quot;vertical-align:top; text-align:left&amp;quot;&lt;br /&gt;
| gpu8&lt;br /&gt;
| gpu801&lt;br /&gt;
| time=30, mem-per-cpu=5000mb, cpus-per-gpu=8&lt;br /&gt;
| time=48:00:00, mem=752000mb, ntasks-per-node=96&lt;br /&gt;
|- &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Default resources of a queue class defines time, #tasks and memory if not explicitly given with sbatch command. Resource list acronyms &amp;lt;code&amp;gt;--time&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--ntasks&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--nodes&amp;lt;/code&amp;gt;, &amp;lt;code&amp;gt;--mem&amp;lt;/code&amp;gt; and &amp;lt;code&amp;gt;--mem-per-cpu&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
A typical Slurm batch script (called for brevity &amp;lt;code&amp;gt;python_run.slurm&amp;lt;/code&amp;gt;) for 1-node requiring one NVIDIA L40S GPU:&lt;br /&gt;
 #!/bin/bash&lt;br /&gt;
 #SBATCH --partition=gpu1&lt;br /&gt;
 #SBATCH --ntasks-per-gpu=48&lt;br /&gt;
 #SBATCH --gres=gpu:1&lt;br /&gt;
 #SBATCH --time=1:00:00&lt;br /&gt;
 #SBATCH --mail-type=all&lt;br /&gt;
 #SBATCH --mail-user=my_email@hs-esslingen.de&lt;br /&gt;
 module load devel/cuda/12.4&lt;br /&gt;
 cd $TMPDIR&lt;br /&gt;
 python3 -m venv my_environment&lt;br /&gt;
 . my_environment/bin/activate&lt;br /&gt;
 python3 -m pip install -r $HOME/my_requirements.txt&lt;br /&gt;
 rsync -avz $HOME/my_data_dir/ .&lt;br /&gt;
 time python3 $HOME/python_script.py&lt;br /&gt;
&lt;br /&gt;
Submitting &amp;lt;code&amp;gt;sbatch python_run.slurm&amp;lt;/code&amp;gt; will allocate one compute node and allocate the one available GPU for 1 hour. Furthermore, this will load the CUDA module version 12.4. It will then change to the &#039;&#039;&#039;fast&#039;&#039;&#039; scratch directory specified in the environment variable &amp;lt;code&amp;gt;TMPDIR&amp;lt;/code&amp;gt;.&lt;br /&gt;
You &#039;&#039;&#039;have&#039;&#039;&#039; to allocate the GPU, otherwise You may not use it.&lt;br /&gt;
It will then follow Python&#039;s best practices and create a new Virtual Environment in that directory, then installing the dependencies of the projects detailed in &amp;lt;code&amp;gt;my_requirements.txt&amp;lt;/code&amp;gt;&lt;br /&gt;
It then copies the data directory in &amp;lt;code&amp;gt;my_data_dir&amp;lt;/code&amp;gt; to this directory using &amp;lt;code&amp;gt;rsync&amp;lt;/code&amp;gt;.&lt;br /&gt;
Finally, it executes your main python script, using the time command to figure out, how much time actually was used.&lt;br /&gt;
Alternatively you may time all the commands to get an estimate for Your next batch job.&lt;br /&gt;
&lt;br /&gt;
Here, Slurm will email to the specified address upon start and completion of the job with a summary.&lt;br /&gt;
&lt;br /&gt;
The &#039;&#039;&#039;better&#039;&#039;&#039; your approximation, the better the Slurm scheduler may allocate resources to all users.&lt;br /&gt;
&lt;br /&gt;
== Interactive usage ==&lt;br /&gt;
To &#039;&#039;&#039;get a good estimation&#039;&#039;&#039; of runtime, You may first want to try the resource &#039;&#039;interactively&#039;&#039;:&lt;br /&gt;
    srun --partition=gpu1 --ntasks-per-gpu=48 --gres=gpu:1 --pty /bin/bash&lt;br /&gt;
&lt;br /&gt;
Then You may execute the steps in &amp;lt;code&amp;gt;python_run.slurm&amp;lt;/code&amp;gt; script interactively, noting differences and amend your Slurm batch script.&lt;br /&gt;
&#039;&#039;Please note&#039;&#039; the &amp;lt;code&amp;gt;--pty&amp;lt;/code&amp;gt; which forwards the standard output and takes standard input to allow working with the Shell.&lt;br /&gt;
&lt;br /&gt;
== Multiple nodes ==&lt;br /&gt;
Of course You may allocate multiple GPUs across nodes running:&lt;br /&gt;
    sbatch --nodes 4 ./python_run.slurm&lt;br /&gt;
Please be aware, that TMPDIR is still local. For the time being run from Your $HOME or better yet from an allocated [[Workspace]].&lt;br /&gt;
&lt;br /&gt;
== Nodes with multiple GPUs == &lt;br /&gt;
The partitions &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt; and &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt; feature multiple GPUs.&lt;br /&gt;
The &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt; partition contains the node &amp;lt;code&amp;gt;gpu401&amp;lt;/code&amp;gt; featuring 4x AMD MI300A APUs each with 128GB of fast HMB3e memory shared between the 24 cores and the GPU.&lt;br /&gt;
You may use AMD&#039;s ROCm employing HIP, OpenACC or OpenCL to parallelize for the GPU. Please refer to the documentation on this node.&lt;br /&gt;
&lt;br /&gt;
The &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt; partition contains the node &amp;lt;code&amp;gt;gpu801&amp;lt;/code&amp;gt; featuring 8x NVIDIA H100 offering 80GB of VRAM each, interconnected using SXM5.&lt;br /&gt;
Please refer to the documentation on this node.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15506</id>
		<title>DACHS</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15506"/>
		<updated>2025-11-25T07:31:00Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{| style=&amp;quot;width: 100%; border-spacing: 5px;&amp;quot;&lt;br /&gt;
| style=&amp;quot;text-align:center; color:#000;vertical-align:middle;font-size:75%;&amp;quot; |&lt;br /&gt;
[[File:DACHS_Logo.png|center|border|250px||]] &lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) supports data scientists, machine learning experts and in general engineers for research and education, specifically teaching of the participating Universities of Applied Science.&lt;br /&gt;
&lt;br /&gt;
You can always reach us via Email at [mailto:dachs-admin@hs-esslingen.de dachs-admin@hs-esslingen.de].&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;  background:#eeeefe; width:100%;&amp;quot; &lt;br /&gt;
| style=&amp;quot;padding:8px; background:#dedefe; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Training &amp;amp; Support&lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
* [[DACHS/Getting_Started|Getting Started]]&lt;br /&gt;
&amp;lt;!-- * [http://dachs.hs-esslingen.de/ Cluster Status and Usage] --&amp;gt;&lt;br /&gt;
* [https://training.bwhpc.de E-Learning Courses]&lt;br /&gt;
* [[DACHS/Support|Contact and Support]]&lt;br /&gt;
* Send [[:Category:Feedback|Feedback]] about Wiki pages&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#cef2e0; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | User Documentation&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* [[DACHS/Registration|Registration]]&lt;br /&gt;
* [[DACHS/Login|Login]]&lt;br /&gt;
* [[DACHS/Hardware|Hardware and Architecture]]&lt;br /&gt;
* Usage of [[DACHS/Software|Software]] on DACHS&lt;br /&gt;
* Running Jobs&lt;br /&gt;
** [[DACHS/Quickstart Slurm]]&lt;br /&gt;
** [[BwUniCluster2.0/Slurm|Slurm Batch System]] (page of bwUniCluster2.0)&lt;br /&gt;
** [[DACHS/Queues|Queues]]&lt;br /&gt;
** [[DACHS/Jupyter|Interactive Computing with Jupyter]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
{| style=&amp;quot;  background:#e6e9eb; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#d1dadf; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Cluster Funding&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* Please [[DACHS/Acknowledgement|acknowledge]] the cluster in your publications.&lt;br /&gt;
|}&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Hardware_and_Architecture&amp;diff=15505</id>
		<title>DACHS/Hardware and Architecture</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Hardware_and_Architecture&amp;diff=15505"/>
		<updated>2025-11-25T07:30:32Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: M Kunzelmann moved page DACHS/Hardware and Architecture to DACHS/Hardware&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;#REDIRECT [[DACHS/Hardware]]&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Hardware&amp;diff=15504</id>
		<title>DACHS/Hardware</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Hardware&amp;diff=15504"/>
		<updated>2025-11-25T07:30:32Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: M Kunzelmann moved page DACHS/Hardware and Architecture to DACHS/Hardware&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;= Architecture of DACHS =&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) is a parallel computer with distributed memory connected over Infiniband and Ethernet. The compute nodes contain at least dual AMD processors, at least 384GB of local memory, 2 TB local NVMe-based disc storage and accelerators as shown in the table below. With BeeGFS a fast and scalable filesystem is provided via Infiniband to all login and compute nodes&lt;br /&gt;
&lt;br /&gt;
The Operating System is Rocky-Linux 9.4 (which is based on RHEL).&lt;br /&gt;
The setup is kept in-line (with regard to Software, Setup and general usage) and thus mostly equivalent to bwHPC and bwUniCluster in particular.&lt;br /&gt;
&lt;br /&gt;
= Components of DACHS =&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
|- &lt;br /&gt;
! style=&amp;quot;width:9%&amp;quot;|&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;L40S&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;H100&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Compute nodes &amp;quot;AMD_APU&amp;quot;&lt;br /&gt;
! style=&amp;quot;width:13%&amp;quot;| Login&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Availability in Queue&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt;&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt;&lt;br /&gt;
| &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt;&lt;br /&gt;
|&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Number of nodes&lt;br /&gt;
| 45&lt;br /&gt;
| 1&lt;br /&gt;
| 1&lt;br /&gt;
| 2&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Processors&lt;br /&gt;
| AMD EPYC 9254&lt;br /&gt;
| AMD EPYC 9454&lt;br /&gt;
| AMD MI300A&lt;br /&gt;
| AMD EPYC 9254&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Number of sockets&lt;br /&gt;
| 2&lt;br /&gt;
| 2&lt;br /&gt;
| 4&lt;br /&gt;
| 2&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Processor frequency (GHz)&lt;br /&gt;
| 2.9 Ghz&lt;br /&gt;
| 2.75 Ghz&lt;br /&gt;
| 2.1 Ghz&lt;br /&gt;
| 2.9 Ghz&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Total number of cores&lt;br /&gt;
| 48&lt;br /&gt;
| 96&lt;br /&gt;
| 96&lt;br /&gt;
| 48&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Main memory&lt;br /&gt;
| 384 GB&lt;br /&gt;
| 1536 GB&lt;br /&gt;
| 512 GB&lt;br /&gt;
| 384 GB&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Local SSD&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
| 1,92 TB NVMe&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Accelerators&lt;br /&gt;
| 1x NVIDIA L40S&lt;br /&gt;
| 8x NVIDIA H100&lt;br /&gt;
| 4x AMD MI300A&lt;br /&gt;
| -&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Accelerator memory&lt;br /&gt;
| 48 GB&lt;br /&gt;
| 8x 80 GB&lt;br /&gt;
| 4x 128 GB&lt;br /&gt;
| -&lt;br /&gt;
|-&lt;br /&gt;
!scope=&amp;quot;column&amp;quot;| Interconnect&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
| IB HDR100&lt;br /&gt;
|}&lt;br /&gt;
Table 1: Properties of the nodes&lt;br /&gt;
&lt;br /&gt;
== Storage Architecture ==&lt;br /&gt;
The system features a 700 TB large BeeGFS filesystem available on login and compute nodes.&lt;br /&gt;
Please note: there is a hard file size quota per partner organization and a soft quota per user on Your HOME.&lt;br /&gt;
Users will be notified by E-Mail if the quota is to be reached.&lt;br /&gt;
&lt;br /&gt;
Please &#039;&#039;&#039;do make usage&#039;&#039;&#039; of [[Workspace | Work Space mechanism]] for larger files.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Quickstart_Slurm&amp;diff=15503</id>
		<title>DACHS/Quickstart Slurm</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Quickstart_Slurm&amp;diff=15503"/>
		<updated>2025-11-25T07:28:41Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: Created page with &amp;quot;&amp;lt;span id=&amp;quot;quickstart&amp;quot;&amp;gt;&amp;lt;/span&amp;gt; = Quickstart =  &amp;lt;span id=&amp;quot;contact-and-further-links-to-bwhpc-wiki&amp;quot;&amp;gt;&amp;lt;/span&amp;gt; == Contact and Further Links to bwHPC wiki ==  If you don&amp;#039;t find the information you need in this wiki, you can always reach us at [mailto:dachs-admin@hs-esslingen.de dachs-admin@hs-esslingen.de].  &amp;lt;span id=&amp;quot;typical-sbatch-script&amp;quot;&amp;gt;&amp;lt;/span&amp;gt; == Typical SBATCH script ==  This is just a brief guide to get you started. All queues, limits, and hardware are documented in deta...&amp;quot;&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&amp;lt;span id=&amp;quot;quickstart&amp;quot;&amp;gt;&amp;lt;/span&amp;gt;&lt;br /&gt;
= Quickstart =&lt;br /&gt;
&lt;br /&gt;
&amp;lt;span id=&amp;quot;contact-and-further-links-to-bwhpc-wiki&amp;quot;&amp;gt;&amp;lt;/span&amp;gt;&lt;br /&gt;
== Contact and Further Links to bwHPC wiki ==&lt;br /&gt;
&lt;br /&gt;
If you don&#039;t find the information you need in this wiki, you can always reach us at [mailto:dachs-admin@hs-esslingen.de dachs-admin@hs-esslingen.de].&lt;br /&gt;
&lt;br /&gt;
&amp;lt;span id=&amp;quot;typical-sbatch-script&amp;quot;&amp;gt;&amp;lt;/span&amp;gt;&lt;br /&gt;
== Typical SBATCH script ==&lt;br /&gt;
&lt;br /&gt;
This is just a brief guide to get you started. All queues, limits, and hardware are documented in detail at the [[DACHS/Hardware]].&lt;br /&gt;
&lt;br /&gt;
Our default queue is &amp;lt;code&amp;gt;gpu1&amp;lt;/code&amp;gt; that you specify with &amp;lt;code&amp;gt;--partition=gpu1&amp;lt;/code&amp;gt; explicitly. Other queues are &amp;lt;code&amp;gt;gpu4&amp;lt;/code&amp;gt; (4 AMD MI300A APUs) and &amp;lt;code&amp;gt;gpu8&amp;lt;/code&amp;gt; (8 NVIDIA H100 GPUs). For more deatiled information, visit [https://wiki.bwhpc.de/e/DACHS/Queues DACHS/Queues].&lt;br /&gt;
&lt;br /&gt;
This is the content of &amp;lt;code&amp;gt;testjob.sh&amp;lt;/code&amp;gt;. It is basically a Bash script with some instructions in the format of comment for the Slurm scheduler.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;#!/bin/bash&lt;br /&gt;
#SBATCH --ntasks=1       # allocate 1 CPU&lt;br /&gt;
#SBATCH --time=30:00     # time limit of 30 min&lt;br /&gt;
#SBATCH --mem=42gb       # allocate 42 GB RAM&lt;br /&gt;
#SBATch --gres=gpu:1     # allocate one GPU&lt;br /&gt;
#SBATCH --job-name=&amp;quot;CHANGEME job name&amp;quot;&lt;br /&gt;
# Uncomment the following lines to get email notifications about your job&lt;br /&gt;
# #SBATCH --mail-type=ALL  # list of &amp;quot;ALL,START,END&lt;br /&gt;
# #SBATCH --mail-user=CHANGME@EMAIL.COM&lt;br /&gt;
&lt;br /&gt;
# You Shell script that setups your job and starts your work is here.&lt;br /&gt;
# That might include loading a module from provided software (check with&lt;br /&gt;
# `module avail` or sourcing a Python environment.&lt;br /&gt;
&lt;br /&gt;
# Load Python 3.13.3 compiled with gnu 14.2&lt;br /&gt;
module load devel/python/3.13.3-gnu-14.2&lt;br /&gt;
&lt;br /&gt;
# Run your Python script that you previously prepared on the Login node.&lt;br /&gt;
uv run python3 main.py&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
For a detailed overview of slurm visit the [https://wiki.bwhpc.de/e/BwUniCluster2.0/Slurm SBATCH options and Slurm wiki page].&lt;br /&gt;
&lt;br /&gt;
You can display available nodes by running&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;sinfo_t_idle&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
&lt;br /&gt;
Submit your job:&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;sbatch testjob.sh&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
&lt;br /&gt;
When you queued a job, you can show its status:&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;squeue&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
If resources are not immediately available add &amp;lt;code&amp;gt;--start&amp;lt;/code&amp;gt; to show its expected start time:&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;squeue --start&amp;lt;/syntaxhighlight&amp;gt;&lt;br /&gt;
If you want to cancel your job run&lt;br /&gt;
&lt;br /&gt;
&amp;lt;syntaxhighlight lang=&amp;quot;sh&amp;quot;&amp;gt;scancel &amp;lt;jobid&amp;gt;&amp;lt;/syntaxhighlight&amp;gt;&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15502</id>
		<title>DACHS</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15502"/>
		<updated>2025-11-25T07:17:26Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{| style=&amp;quot;width: 100%; border-spacing: 5px;&amp;quot;&lt;br /&gt;
| style=&amp;quot;text-align:center; color:#000;vertical-align:middle;font-size:75%;&amp;quot; |&lt;br /&gt;
[[File:DACHS_Logo.png|center|border|250px||]] &lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) supports data scientists, machine learning experts and in general engineers for research and education, specifically teaching of the participating Universities of Applied Science.&lt;br /&gt;
&lt;br /&gt;
You can always reach us via Email at [mailto:dachs-admin@hs-esslingen.de dachs-admin@hs-esslingen.de].&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;  background:#eeeefe; width:100%;&amp;quot; &lt;br /&gt;
| style=&amp;quot;padding:8px; background:#dedefe; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Training &amp;amp; Support&lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
* [[DACHS/Getting_Started|Getting Started]]&lt;br /&gt;
&amp;lt;!-- * [http://dachs.hs-esslingen.de/ Cluster Status and Usage] --&amp;gt;&lt;br /&gt;
* [https://training.bwhpc.de E-Learning Courses]&lt;br /&gt;
* [[DACHS/Support|Contact and Support]]&lt;br /&gt;
* Send [[:Category:Feedback|Feedback]] about Wiki pages&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#cef2e0; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | User Documentation&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* [[DACHS/Registration|Registration]]&lt;br /&gt;
* [[DACHS/Login|Login]]&lt;br /&gt;
* [[DACHS/Hardware_and_Architecture|Hardware and Architecture]]&lt;br /&gt;
* Usage of [[DACHS/Software|Software]] on DACHS&lt;br /&gt;
* Running Jobs&lt;br /&gt;
** [[DACHS/Quickstart Slurm]]&lt;br /&gt;
** [[BwUniCluster2.0/Slurm|Slurm Batch System]] (page of bwUniCluster2.0)&lt;br /&gt;
** [[DACHS/Queues|Queues]]&lt;br /&gt;
** [[DACHS/Jupyter|Interactive Computing with Jupyter]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
{| style=&amp;quot;  background:#e6e9eb; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#d1dadf; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Cluster Funding&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* Please [[DACHS/Acknowledgement|acknowledge]] the cluster in your publications.&lt;br /&gt;
|}&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Software&amp;diff=15408</id>
		<title>DACHS/Software</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Software&amp;diff=15408"/>
		<updated>2025-11-17T11:44:46Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;For available Software Modules, please [[DACHS/Login|login via SSH]] described above and type &amp;lt;code&amp;gt;module avail&amp;lt;/code&amp;gt;.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Software&amp;diff=15407</id>
		<title>DACHS/Software</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Software&amp;diff=15407"/>
		<updated>2025-11-17T11:43:52Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;For available Software Modules, please login via SSH described above and type &amp;lt;code&amp;gt;module avail&amp;lt;/code&amp;gt;.&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Software&amp;diff=15406</id>
		<title>DACHS/Software</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Software&amp;diff=15406"/>
		<updated>2025-11-17T11:41:51Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: Created page with &amp;quot;For available Software Modules, please login via SSH described above and type &amp;#039;&amp;#039;module avail&amp;#039;&amp;#039;&amp;quot;&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;For available Software Modules, please login via SSH described above and type &#039;&#039;module avail&#039;&#039;&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15405</id>
		<title>DACHS</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15405"/>
		<updated>2025-11-17T11:41:09Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{| style=&amp;quot;width: 100%; border-spacing: 5px;&amp;quot;&lt;br /&gt;
| style=&amp;quot;text-align:center; color:#000;vertical-align:middle;font-size:75%;&amp;quot; |&lt;br /&gt;
[[File:DACHS_Logo.png|center|border|250px||]] &lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) supports data scientists, machine learning experts and in general engineers for research and education, specifically teaching of the participating Universities of Applied Science.&lt;br /&gt;
&lt;br /&gt;
You can always reach us via Email at [mailto:dachs-admin@hs-esslingen.de dachs-admin@hs-esslingen.de].&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;  background:#eeeefe; width:100%;&amp;quot; &lt;br /&gt;
| style=&amp;quot;padding:8px; background:#dedefe; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Training &amp;amp; Support&lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
* [[DACHS/Getting_Started|Getting Started]]&lt;br /&gt;
&amp;lt;!-- * [http://dachs.hs-esslingen.de/ Cluster Status and Usage] --&amp;gt;&lt;br /&gt;
* [https://training.bwhpc.de E-Learning Courses]&lt;br /&gt;
* [[DACHS/Support|Contact and Support]]&lt;br /&gt;
* Send [[:Category:Feedback|Feedback]] about Wiki pages&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#cef2e0; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | User Documentation&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* [[DACHS/Registration|Registration]]&lt;br /&gt;
* [[DACHS/Login|Login]]&lt;br /&gt;
* [[DACHS/Hardware_and_Architecture|Hardware and Architecture]]&lt;br /&gt;
* Usage of [[DACHS/Software|Software]] on DACHS&lt;br /&gt;
* [[BwUniCluster2.0/Slurm|Batch System]] (page of bwUniCluster2.0)&lt;br /&gt;
** [[DACHS/Queues|Queues]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
{| style=&amp;quot;  background:#e6e9eb; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#d1dadf; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Cluster Funding&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* Please [[DACHS/Acknowledgement|acknowledge]] the cluster in your publications.&lt;br /&gt;
|}&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15389</id>
		<title>DACHS</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15389"/>
		<updated>2025-11-12T12:06:51Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{| style=&amp;quot;width: 100%; border-spacing: 5px;&amp;quot;&lt;br /&gt;
| style=&amp;quot;text-align:center; color:#000;vertical-align:middle;font-size:75%;&amp;quot; |&lt;br /&gt;
[[File:DACHS_Logo.png|center|border|250px||]] &lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) supports data scientists, machine learning experts and in general engineers for research and education, specifically teaching of the participating Universities of Applied Science.&lt;br /&gt;
&lt;br /&gt;
You can always reach us via Email at [mailto:dachs-admin@hs-esslingen.de dachs-admin@hs-esslingen.de].&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;  background:#eeeefe; width:100%;&amp;quot; &lt;br /&gt;
| style=&amp;quot;padding:8px; background:#dedefe; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Training &amp;amp; Support&lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
* [[DACHS/Getting_Started|Getting Started]]&lt;br /&gt;
&amp;lt;!-- * [http://dachs.hs-esslingen.de/ Cluster Status and Usage] --&amp;gt;&lt;br /&gt;
* [https://training.bwhpc.de E-Learning Courses]&lt;br /&gt;
* [[DACHS/Support|Contact and Support]]&lt;br /&gt;
* Send [[:Category:Feedback|Feedback]] about Wiki pages&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#cef2e0; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | User Documentation&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* [[DACHS/Registration|Registration]]&lt;br /&gt;
* [[DACHS/Login|Login]]&lt;br /&gt;
* [[DACHS/Hardware_and_Architecture|Hardware and Architecture]]&lt;br /&gt;
* Usage of [[DACHS/Software|Software]] on DACHS&lt;br /&gt;
** For available Software Modules, please login as described above and type ``module avail``&lt;br /&gt;
* [[BwUniCluster2.0/Slurm|Batch System]] (page of bwUniCluster2.0)&lt;br /&gt;
** [[DACHS/Queues|Queues]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
{| style=&amp;quot;  background:#e6e9eb; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#d1dadf; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Cluster Funding&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* Please [[DACHS/Acknowledgement|acknowledge]] the cluster in your publications.&lt;br /&gt;
|}&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15388</id>
		<title>DACHS</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15388"/>
		<updated>2025-11-12T12:06:32Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{| style=&amp;quot;width: 100%; border-spacing: 5px;&amp;quot;&lt;br /&gt;
| style=&amp;quot;text-align:center; color:#000;vertical-align:middle;font-size:75%;&amp;quot; |&lt;br /&gt;
[[File:DACHS_Logo.png|center|border|250px||]] &lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) supports data scientists, machine learning experts and in general engineers for research and education, specifically teaching of the participating Universities of Applied Science.&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;  background:#eeeefe; width:100%;&amp;quot; &lt;br /&gt;
| style=&amp;quot;padding:8px; background:#dedefe; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Training &amp;amp; Support&lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
* [[DACHS/Getting_Started|Getting Started]]&lt;br /&gt;
&amp;lt;!-- * [http://dachs.hs-esslingen.de/ Cluster Status and Usage] --&amp;gt;&lt;br /&gt;
* [https://training.bwhpc.de E-Learning Courses]&lt;br /&gt;
* [[DACHS/Support|Contact and Support]]&lt;br /&gt;
* Send [[:Category:Feedback|Feedback]] about Wiki pages&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#cef2e0; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | User Documentation&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* [[DACHS/Registration|Registration]]&lt;br /&gt;
* [[DACHS/Login|Login]]&lt;br /&gt;
* [[DACHS/Hardware_and_Architecture|Hardware and Architecture]]&lt;br /&gt;
* Usage of [[DACHS/Software|Software]] on DACHS&lt;br /&gt;
** For available Software Modules, please login as described above and type ``module avail``&lt;br /&gt;
* [[BwUniCluster2.0/Slurm|Batch System]] (page of bwUniCluster2.0)&lt;br /&gt;
** [[DACHS/Queues|Queues]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
{| style=&amp;quot;  background:#e6e9eb; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#d1dadf; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Cluster Funding&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* Please [[DACHS/Acknowledgement|acknowledge]] the cluster in your publications.&lt;br /&gt;
|}&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15387</id>
		<title>DACHS</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15387"/>
		<updated>2025-11-12T12:06:03Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{| style=&amp;quot;width: 100%; border-spacing: 5px;&amp;quot;&lt;br /&gt;
| style=&amp;quot;text-align:center; color:#000;vertical-align:middle;font-size:75%;&amp;quot; |&lt;br /&gt;
[[File:DACHS_Logo.png|center|border|250px||]] &lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) supports data scientists, machine learning experts and in general engineers for research and education, specifically teaching of the participating Universities of Applied Science.&lt;br /&gt;
&lt;br /&gt;
You can always reach us via Email at [mailto:dachs-admin@hs-esslingen.de dachs-admin@hs-esslingen.de].&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;  background:#eeeefe; width:100%;&amp;quot; &lt;br /&gt;
| style=&amp;quot;padding:8px; background:#dedefe; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Training &amp;amp; Support&lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
* [[DACHS/Getting_Started|Getting Started]]&lt;br /&gt;
&amp;lt;!-- * [http://dachs.hs-esslingen.de/ Cluster Status and Usage] --&amp;gt;&lt;br /&gt;
* [https://training.bwhpc.de E-Learning Courses]&lt;br /&gt;
* [[DACHS/Support|Contact and Support]]&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#cef2e0; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | User Documentation&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* [[DACHS/Registration|Registration]]&lt;br /&gt;
* [[DACHS/Login|Login]]&lt;br /&gt;
* [[DACHS/Hardware_and_Architecture|Hardware and Architecture]]&lt;br /&gt;
* Usage of [[DACHS/Software|Software]] on DACHS&lt;br /&gt;
** For available Software Modules, please login as described above and type ``module avail``&lt;br /&gt;
* [[BwUniCluster2.0/Slurm|Batch System]] (page of bwUniCluster2.0)&lt;br /&gt;
** [[DACHS/Queues|Queues]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
{| style=&amp;quot;  background:#e6e9eb; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#d1dadf; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Cluster Funding&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* Please [[DACHS/Acknowledgement|acknowledge]] the cluster in your publications.&lt;br /&gt;
|}&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15386</id>
		<title>DACHS</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15386"/>
		<updated>2025-11-12T12:00:26Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{| style=&amp;quot;width: 100%; border-spacing: 5px;&amp;quot;&lt;br /&gt;
| style=&amp;quot;text-align:center; color:#000;vertical-align:middle;font-size:75%;&amp;quot; |&lt;br /&gt;
[[File:DACHS_Logo.png|center|border|250px||]] &lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (DACHS) supports data scientists, machine learning experts and in general engineers for research and education, specifically teaching of the participating Universities of Applied Science.&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;  background:#eeeefe; width:100%;&amp;quot; &lt;br /&gt;
| style=&amp;quot;padding:8px; background:#dedefe; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Training &amp;amp; Support&lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
* [[DACHS/Getting_Started|Getting Started]]&lt;br /&gt;
&amp;lt;!-- * [http://dachs.hs-esslingen.de/ Cluster Status and Usage] --&amp;gt;&lt;br /&gt;
* [https://training.bwhpc.de E-Learning Courses]&lt;br /&gt;
* [[DACHS/Support|Contact and Support]]&lt;br /&gt;
* Send [[:Category:Feedback|Feedback]] about Wiki pages&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#cef2e0; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | User Documentation&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* [[DACHS/Registration|Registration]]&lt;br /&gt;
* [[DACHS/Login|Login]]&lt;br /&gt;
* [[DACHS/Hardware_and_Architecture|Hardware and Architecture]]&lt;br /&gt;
* Usage of [[DACHS/Software|Software]] on DACHS&lt;br /&gt;
** For available Software Modules, please login as described above and type ``module avail``&lt;br /&gt;
* [[BwUniCluster2.0/Slurm|Batch System]] (page of bwUniCluster2.0)&lt;br /&gt;
** [[DACHS/Queues|Queues]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
{| style=&amp;quot;  background:#e6e9eb; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#d1dadf; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Cluster Funding&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* Please [[DACHS/Acknowledgement|acknowledge]] the cluster in your publications.&lt;br /&gt;
|}&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15385</id>
		<title>DACHS</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS&amp;diff=15385"/>
		<updated>2025-11-12T11:57:13Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{| style=&amp;quot;width: 100%; border-spacing: 5px;&amp;quot;&lt;br /&gt;
| style=&amp;quot;text-align:center; color:#000;vertical-align:middle;font-size:75%;&amp;quot; |&lt;br /&gt;
[[File:DACHS_Logo.png|center|border|250px||]] &lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The Datenanalyse Cluster der Hochschulen (short DACHS) supports data scientists, machine learning experts and in general engineers for research and education, specifically teaching of the participating Universities of Applied Science.&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;  background:#eeeefe; width:100%;&amp;quot; &lt;br /&gt;
| style=&amp;quot;padding:8px; background:#dedefe; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Training &amp;amp; Support&lt;br /&gt;
|-&lt;br /&gt;
| &lt;br /&gt;
* [[DACHS/Getting_Started|Getting Started]]&lt;br /&gt;
&amp;lt;!-- * [http://dachs.hs-esslingen.de/ Cluster Status and Usage] --&amp;gt;&lt;br /&gt;
* [https://training.bwhpc.de E-Learning Courses]&lt;br /&gt;
* [[DACHS/Support|Contact and Support]]&lt;br /&gt;
* Send [[:Category:Feedback|Feedback]] about Wiki pages&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#cef2e0; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | User Documentation&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* [[DACHS/Registration|Registration]]&lt;br /&gt;
* [[DACHS/Login|Login]]&lt;br /&gt;
* [[DACHS/Hardware_and_Architecture|Hardware and Architecture]]&lt;br /&gt;
* Usage of [[DACHS/Software|Software]] on DACHS&lt;br /&gt;
** For available Software Modules, please login as described above and type ``module avail``&lt;br /&gt;
* [[BwUniCluster2.0/Slurm|Batch System]] (page of bwUniCluster2.0)&lt;br /&gt;
** [[DACHS/Queues|Queues]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
|}&lt;br /&gt;
{| style=&amp;quot;  background:#e6e9eb; width:100%;&amp;quot;&lt;br /&gt;
| style=&amp;quot;padding:8px; background:#d1dadf; font-size:120%; font-weight:bold;  text-align:left&amp;quot; | Cluster Funding&lt;br /&gt;
|-&lt;br /&gt;
|&lt;br /&gt;
* Please [[DACHS/Acknowledgement|acknowledge]] the cluster in your publications.&lt;br /&gt;
|}&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Login&amp;diff=13715</id>
		<title>DACHS/Login</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Login&amp;diff=13715"/>
		<updated>2025-01-30T12:24:01Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: add link to page to check whether the registered 2FA token works&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to DACHS is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All home institutions of our current users are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect to DACHS without restrictions.&lt;br /&gt;
If you are outside one of the BelWü networks (e.g. at home), a VPN connection to the home institution or a connection to an SSH jump host at the home institution must be established first.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The login nodes of the DACHS cluster are the access points to the compute system, your &amp;lt;code&amp;gt;$HOME&amp;lt;/code&amp;gt; directory and your workspaces.&lt;br /&gt;
All users must log in through these nodes to submit jobs to the cluster.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Prerequisites for successful login:&#039;&#039;&#039;&lt;br /&gt;
&lt;br /&gt;
You need to have&lt;br /&gt;
* completed the 3-step [[registration]] procedure.&lt;br /&gt;
* [[Registration/Password|set a service password]] for DACHS.&lt;br /&gt;
* [[Registration/2FA|set up a second factor]] for the time-based one-time password (TOTP).&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login to the DACHS =&lt;br /&gt;
&lt;br /&gt;
Login to the DACHS is only possible with a Secure Shell (SSH) client for which you must know your username on the cluster and the hostname of the login nodes.&lt;br /&gt;
For more general information on SSH clients, visit the [[Registration/Login/Client|SSH clients Guide]].&lt;br /&gt;
&lt;br /&gt;
== Username ==&lt;br /&gt;
&lt;br /&gt;
If you want to use DACHS, you need to add a prefix to your local username: &amp;lt;code&amp;gt;prefix_username&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! University !! Prefix&lt;br /&gt;
|-&lt;br /&gt;
| HS Aalen || aa&lt;br /&gt;
|-&lt;br /&gt;
| HS Albstadt-Sigmaringen || as&lt;br /&gt;
|-&lt;br /&gt;
| HS Esslingen || es&lt;br /&gt;
|-&lt;br /&gt;
| HS Heilbronn || hn&lt;br /&gt;
|-&lt;br /&gt;
| HS Karlsruhe || hk&lt;br /&gt;
|-&lt;br /&gt;
| HTWG Konstanz || ht&lt;br /&gt;
|-&lt;br /&gt;
| HS Mannheim || mn&lt;br /&gt;
|-&lt;br /&gt;
| HS Offenburg || of&lt;br /&gt;
|-&lt;br /&gt;
| HS Reutlingen || hr&lt;br /&gt;
|-&lt;br /&gt;
| HfT-Stuttgart || hs&lt;br /&gt;
|-&lt;br /&gt;
| THU-Ulm || hu&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
For a full list of user names, you can check the [https://www.bwidm.de/hochschulen.php bwIDM Hochschulen page].&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Example:&#039;&#039;&#039;&amp;lt;br/&amp;gt;&lt;br /&gt;
If your local username for the University is &amp;lt;code&amp;gt;vwxyz1234&amp;lt;/code&amp;gt; and you are a user from the University of Esslingen this would combine to: &amp;lt;code&amp;gt;es_vwxyz1234&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
== Hostnames ==&lt;br /&gt;
&lt;br /&gt;
The system has two login nodes.&lt;br /&gt;
The selection of the login node is done automatically.&lt;br /&gt;
If you are logging in multiple times, different sessions might run on different login nodes.&lt;br /&gt;
&lt;br /&gt;
Login to DACHS:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Hostname !! Node type&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login.hs-esslingen.de&#039;&#039;&#039; || login to one of the two login nodes&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
In general, you should use automatic selection to allow us to balance the load over the two login nodes.&lt;br /&gt;
If you need to connect to specific login node, you can use the following hostnames:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Hostname !! Node type&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login1.hs-esslingen.de&#039;&#039;&#039; || DACHS first login node&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login2.hs-esslingen.de&#039;&#039;&#039; || DACHS second login node&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
If you explicitly connect to dachs-login1 but end up on dachs-login2 (or the other way around), then of of them might not be available at the time and you&#039;re automatically redirected to the other one.&lt;br /&gt;
&lt;br /&gt;
== Host Keys ==&lt;br /&gt;
&lt;br /&gt;
When you log in, you may receive the message &amp;lt;code&amp;gt;The authenticity of host &#039;&amp;lt;host address&amp;gt;&#039; can&#039;t be established.&amp;lt;/code&amp;gt; along with the host key fingerprint. This is intended so you can verify the authenticity of the host you are connecting to. Before you continue you should verify, if this fingerprint matches one of the following:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Algorithm !! Fingerprint (SHA256)&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;RSA&#039;&#039;&#039; || SHA256:kdvbATXbd/ggG33G7VEw+O+FpJPcZU6XDeFyWXvBkhc&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;ECDSA&#039;&#039;&#039; || SHA256:4Y/LvkPL9g9DZ8JrmTxXsMTIWyM/u/mEEmSB7S/2yyA&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;ED25519&#039;&#039;&#039; || SHA256:X9eRJepYD3da3BM1pgiWxnvRc/Pt5eBLUr18tDUsZjU&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Login with SSH command (Linux, Mac, Windows) ==&lt;br /&gt;
&lt;br /&gt;
Most Unix and Unix-like operating systems like Linux, Mac OS and *BSD come with a built-in SSH client provided by the OpenSSH project.&lt;br /&gt;
More recent versions of Windows 10 and Windows 11 using the [https://docs.microsoft.com/en-us/windows/wsl/install Windows Subsystem for Linux] (WSL) also come with a built-in OpenSSH client.&lt;br /&gt;
&lt;br /&gt;
For login use one of the following ssh commands:&lt;br /&gt;
&lt;br /&gt;
 ssh &amp;lt;username&amp;gt;@dachs-login.hs-esslingen.de&lt;br /&gt;
 ssh -l &amp;lt;username&amp;gt; dachs-login.hs-esslingen.de&lt;br /&gt;
&lt;br /&gt;
To run graphical applications, you can use the &amp;lt;code&amp;gt;-X&amp;lt;/code&amp;gt; or &amp;lt;code&amp;gt;-Y&amp;lt;/code&amp;gt; flag to &amp;lt;code&amp;gt;ssh&amp;lt;/code&amp;gt;:&lt;br /&gt;
&lt;br /&gt;
 ssh -Y -l &amp;lt;username&amp;gt; dachs-login.hs-esslingen.de&lt;br /&gt;
&lt;br /&gt;
For better performance, we recommend using [[VNC]].&lt;br /&gt;
&lt;br /&gt;
== Login with graphical SSH client (Windows) ==&lt;br /&gt;
&lt;br /&gt;
For Windows we suggest using MobaXterm for login and file transfer.&lt;br /&gt;
 &lt;br /&gt;
Start &#039;&#039;MobaXterm&#039;&#039;, fill in the following fields:&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
Remote name              : dachs-login.hs-esslingen.de&lt;br /&gt;
Specify user name        : &amp;lt;username&amp;gt;&lt;br /&gt;
Port                     : 22&lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
After that click on &#039;ok&#039;. Then a terminal will be opened and there you can enter your credentials.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; When using File transfer with MobaXterm version 23.6 the following configuration change has to be made:&lt;br /&gt;
In the settings in the tab &amp;quot;SSH&amp;quot;, change the option &amp;quot;SSH engine&amp;quot; from &amp;quot;&amp;lt;new&amp;gt;&amp;quot; to &amp;quot;&amp;lt;legacy&amp;gt;&amp;quot;. Then restart MobaXterm&lt;br /&gt;
&lt;br /&gt;
&amp;lt;!-- TODO: We&#039;ll include this when we got Jupyterhub working.&lt;br /&gt;
&lt;br /&gt;
== Login with Jupyterhub ==&lt;br /&gt;
&lt;br /&gt;
TODO: will there be another URL for this? &lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
Login takes place at:&lt;br /&gt;
* bwUniCluster 2.0: [https://uc2-jupyter.scc.kit.edu uc2-jupyter.scc.kit.edu]&lt;br /&gt;
* SDIL: [https://sdil-jupyter.scc.kit.edu sdil-jupyter.scc.kit.edu]&lt;br /&gt;
&lt;br /&gt;
More Information can be found [[BwUniCluster2.0/Jupyter#Login_process|here]].&lt;br /&gt;
&lt;br /&gt;
--&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Login Example ==&lt;br /&gt;
&lt;br /&gt;
To log in to DACHS, you must provide your [[Registration/Password|service password]].&lt;br /&gt;
Proceed as follows:&lt;br /&gt;
# Use SSH for a login node.&lt;br /&gt;
# The system will ask for a one-time password &amp;lt;code&amp;gt;Your OTP:&amp;lt;/code&amp;gt;. Please enter your OTP and confirm it with Enter/Return. If you do not have a second factor yet, please create one (see [[Registration/2FA]]).&lt;br /&gt;
# The system will ask you for your service password &amp;lt;code&amp;gt;Password:&amp;lt;/code&amp;gt;. Please enter it and confirm it with Enter/Return. If you do not have a service password yet or have forgotten it, please create one (see [[Registration/Password]]).&lt;br /&gt;
# You will be greeted by the DACHS cluster, followed by a shell.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
~ $ ssh -l es_vwxyz1234 dachs-login.hs-esslingen.de&lt;br /&gt;
(es_vwxyz1234@dachs-login.hs-esslingen.de) Your OTP: 123456&lt;br /&gt;
(es_vwxyz1234@dachs-login.hs-esslingen.de) Password: &lt;br /&gt;
********************************************************************************&lt;br /&gt;
Last login: Thu Jul  7 18:09:43 2022 from dachs-login.hs-esslingen.de&lt;br /&gt;
********************************************************************************&lt;br /&gt;
[es_vwxyz1234@login1 ~]$ &lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Troubleshooting ==&lt;br /&gt;
&lt;br /&gt;
If your OTP code doesn&#039;t get accepted multiple times in a row, you should first check that the second factor works and is active in the [https://login.bwidm.de/user/twofa.xhtml bwIDM My Tokens section]. &lt;br /&gt;
&lt;br /&gt;
&amp;lt;!-- See [[BwUniCluster_2.0/FAQ#Login_Issues|bwUniCluster FAQ]]. --&amp;gt;&lt;br /&gt;
&lt;br /&gt;
= Allowed Activities on Login Nodes =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
To guarantee usability for all the users of clusters you must not run your compute jobs on the login nodes.&lt;br /&gt;
Compute jobs must be submitted to the queuing system.&lt;br /&gt;
Any compute job running on the login nodes will be terminated without any notice.&lt;br /&gt;
Any long-running compilation or any long-running pre- or post-processing of batch jobs must also be submitted to the queuing system.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The login nodes of the DACHS cluster are the access point to the compute system, your &amp;lt;code&amp;gt;$HOME&amp;lt;/code&amp;gt; directory and your workspaces.&lt;br /&gt;
These nodes are shared with all the users therefore, your activities on the login nodes are limited to primarily set up your batch jobs.&lt;br /&gt;
Your activities may also be:&lt;br /&gt;
* &#039;&#039;&#039;short&#039;&#039;&#039; compilation of your program code and&lt;br /&gt;
* &#039;&#039;&#039;short&#039;&#039;&#039; pre- and post-processing of your batch jobs.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;!--&lt;br /&gt;
TODO:&lt;br /&gt;
We advise users to use [[BwUniCluster_2.0_Batch_Queues#Interactive_Jobs|interactive jobs]] for compute and memory intensive tasks like compiling.&lt;br /&gt;
--&amp;gt;&lt;br /&gt;
&lt;br /&gt;
We advise users to use [[DACHS/Queues|interactive jobs]] for compute and memory intensive tasks like compiling.&lt;br /&gt;
&lt;br /&gt;
= Related Information =&lt;br /&gt;
&lt;br /&gt;
* If you want to reset your service password, consult the [[Registration/Password|Password Guide]].&lt;br /&gt;
* If you want to register a new token for the two factor authentication (2FA), consult the [[Registration/2FA|2FA Guide]].&lt;br /&gt;
* If you want to de-register, consult the [[Registration/Deregistration|De-registration Guide]].&lt;br /&gt;
* If you need an SSH key for your workflow, read [[Registration/SSH|Registering SSH Keys with your Cluster]].&lt;br /&gt;
* Configuring your shell: [[.bashrc Do&#039;s and Don&#039;ts]]&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Login&amp;diff=13530</id>
		<title>DACHS/Login</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Login&amp;diff=13530"/>
		<updated>2024-12-19T15:36:01Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: /* Hostnames */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to DACHS is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All home institutions of our current users are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect to DACHS without restrictions.&lt;br /&gt;
If you are outside one of the BelWü networks (e.g. at home), a VPN connection to the home institution or a connection to an SSH jump host at the home institution must be established first.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The login nodes of the DACHS cluster are the access points to the compute system, your &amp;lt;code&amp;gt;$HOME&amp;lt;/code&amp;gt; directory and your workspaces.&lt;br /&gt;
All users must log in through these nodes to submit jobs to the cluster.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Prerequisites for successful login:&#039;&#039;&#039;&lt;br /&gt;
&lt;br /&gt;
You need to have&lt;br /&gt;
* completed the 3-step [[registration]] procedure.&lt;br /&gt;
* [[Registration/Password|set a service password]] for DACHS.&lt;br /&gt;
* [[Registration/2FA|set up a second factor]] for the time-based one-time password (TOTP).&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login to the DACHS =&lt;br /&gt;
&lt;br /&gt;
Login to the DACHS is only possible with a Secure Shell (SSH) client for which you must know your username on the cluster and the hostname of the login nodes.&lt;br /&gt;
For more general information on SSH clients, visit the [[Registration/Login/Client|SSH clients Guide]].&lt;br /&gt;
&lt;br /&gt;
== Username ==&lt;br /&gt;
&lt;br /&gt;
If you want to use DACHS, you need to add a prefix to your local username: &amp;lt;code&amp;gt;prefix_username&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! University !! Prefix&lt;br /&gt;
|-&lt;br /&gt;
| HS Aalen || aa&lt;br /&gt;
|-&lt;br /&gt;
| HS Albstadt-Sigmaringen || as&lt;br /&gt;
|-&lt;br /&gt;
| HS Esslingen || es&lt;br /&gt;
|-&lt;br /&gt;
| HS Heilbronn || hn&lt;br /&gt;
|-&lt;br /&gt;
| HS Karlsruhe || hk&lt;br /&gt;
|-&lt;br /&gt;
| HTWG Konstanz || ht&lt;br /&gt;
|-&lt;br /&gt;
| HS Mannheim || mn&lt;br /&gt;
|-&lt;br /&gt;
| HS Offenburg || of&lt;br /&gt;
|-&lt;br /&gt;
| HS Reutlingen || hr&lt;br /&gt;
|-&lt;br /&gt;
| HfT-Stuttgart || hs&lt;br /&gt;
|-&lt;br /&gt;
| THU-Ulm || hu&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
For a full list of user names, you can check the [https://www.bwidm.de/hochschulen.php bwIDM Hochschulen page].&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Example:&#039;&#039;&#039;&amp;lt;br/&amp;gt;&lt;br /&gt;
If your local username for the University is &amp;lt;code&amp;gt;vwxyz1234&amp;lt;/code&amp;gt; and you are a user from the University of Esslingen this would combine to: &amp;lt;code&amp;gt;es_vwxyz1234&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
== Hostnames ==&lt;br /&gt;
&lt;br /&gt;
The system has two login nodes.&lt;br /&gt;
The selection of the login node is done automatically.&lt;br /&gt;
If you are logging in multiple times, different sessions might run on different login nodes.&lt;br /&gt;
&lt;br /&gt;
Login to DACHS:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Hostname !! Node type&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login.hs-esslingen.de&#039;&#039;&#039; || login to one of the two login nodes&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
In general, you should use automatic selection to allow us to balance the load over the two login nodes.&lt;br /&gt;
If you need to connect to specific login node, you can use the following hostnames:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Hostname !! Node type&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login1.hs-esslingen.de&#039;&#039;&#039; || DACHS first login node&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login2.hs-esslingen.de&#039;&#039;&#039; || DACHS second login node&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
If you explicitly connect to dachs-login1 but end up on dachs-login2 (or the other way around), then of of them might not be available at the time and you&#039;re automatically redirected to the other one.&lt;br /&gt;
&lt;br /&gt;
== Host Keys ==&lt;br /&gt;
&lt;br /&gt;
When you log in, you may receive the message &amp;lt;code&amp;gt;The authenticity of host &#039;&amp;lt;host address&amp;gt;&#039; can&#039;t be established.&amp;lt;/code&amp;gt; along with the host key fingerprint. This is intended so you can verify the authenticity of the host you are connecting to. Before you continue you should verify, if this fingerprint matches one of the following:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Algorithm !! Fingerprint (SHA256)&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;RSA&#039;&#039;&#039; || SHA256:kdvbATXbd/ggG33G7VEw+O+FpJPcZU6XDeFyWXvBkhc&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;ECDSA&#039;&#039;&#039; || SHA256:4Y/LvkPL9g9DZ8JrmTxXsMTIWyM/u/mEEmSB7S/2yyA&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;ED25519&#039;&#039;&#039; || SHA256:X9eRJepYD3da3BM1pgiWxnvRc/Pt5eBLUr18tDUsZjU&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Login with SSH command (Linux, Mac, Windows) ==&lt;br /&gt;
&lt;br /&gt;
Most Unix and Unix-like operating systems like Linux, Mac OS and *BSD come with a built-in SSH client provided by the OpenSSH project.&lt;br /&gt;
More recent versions of Windows 10 and Windows 11 using the [https://docs.microsoft.com/en-us/windows/wsl/install Windows Subsystem for Linux] (WSL) also come with a built-in OpenSSH client.&lt;br /&gt;
&lt;br /&gt;
For login use one of the following ssh commands:&lt;br /&gt;
&lt;br /&gt;
 ssh &amp;lt;username&amp;gt;@dachs-login.hs-esslingen.de&lt;br /&gt;
 ssh -l &amp;lt;username&amp;gt; dachs-login.hs-esslingen.de&lt;br /&gt;
&lt;br /&gt;
To run graphical applications, you can use the &amp;lt;code&amp;gt;-X&amp;lt;/code&amp;gt; or &amp;lt;code&amp;gt;-Y&amp;lt;/code&amp;gt; flag to &amp;lt;code&amp;gt;ssh&amp;lt;/code&amp;gt;:&lt;br /&gt;
&lt;br /&gt;
 ssh -Y -l &amp;lt;username&amp;gt; dachs-login.hs-esslingen.de&lt;br /&gt;
&lt;br /&gt;
For better performance, we recommend using [[VNC]].&lt;br /&gt;
&lt;br /&gt;
== Login with graphical SSH client (Windows) ==&lt;br /&gt;
&lt;br /&gt;
For Windows we suggest using MobaXterm for login and file transfer.&lt;br /&gt;
 &lt;br /&gt;
Start &#039;&#039;MobaXterm&#039;&#039;, fill in the following fields:&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
Remote name              : dachs-login.hs-esslingen.de&lt;br /&gt;
Specify user name        : &amp;lt;username&amp;gt;&lt;br /&gt;
Port                     : 22&lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
After that click on &#039;ok&#039;. Then a terminal will be opened and there you can enter your credentials.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; When using File transfer with MobaXterm version 23.6 the following configuration change has to be made:&lt;br /&gt;
In the settings in the tab &amp;quot;SSH&amp;quot;, change the option &amp;quot;SSH engine&amp;quot; from &amp;quot;&amp;lt;new&amp;gt;&amp;quot; to &amp;quot;&amp;lt;legacy&amp;gt;&amp;quot;. Then restart MobaXterm&lt;br /&gt;
&lt;br /&gt;
&amp;lt;!-- TODO: We&#039;ll include this when we got Jupyterhub working.&lt;br /&gt;
&lt;br /&gt;
== Login with Jupyterhub ==&lt;br /&gt;
&lt;br /&gt;
TODO: will there be another URL for this? &lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
Login takes place at:&lt;br /&gt;
* bwUniCluster 2.0: [https://uc2-jupyter.scc.kit.edu uc2-jupyter.scc.kit.edu]&lt;br /&gt;
* SDIL: [https://sdil-jupyter.scc.kit.edu sdil-jupyter.scc.kit.edu]&lt;br /&gt;
&lt;br /&gt;
More Information can be found [[BwUniCluster2.0/Jupyter#Login_process|here]].&lt;br /&gt;
&lt;br /&gt;
--&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Login Example ==&lt;br /&gt;
&lt;br /&gt;
To log in to DACHS, you must provide your [[Registration/Password|service password]].&lt;br /&gt;
Proceed as follows:&lt;br /&gt;
# Use SSH for a login node.&lt;br /&gt;
# The system will ask for a one-time password &amp;lt;code&amp;gt;Your OTP:&amp;lt;/code&amp;gt;. Please enter your OTP and confirm it with Enter/Return. If you do not have a second factor yet, please create one (see [[Registration/2FA]]).&lt;br /&gt;
# The system will ask you for your service password &amp;lt;code&amp;gt;Password:&amp;lt;/code&amp;gt;. Please enter it and confirm it with Enter/Return. If you do not have a service password yet or have forgotten it, please create one (see [[Registration/Password]]).&lt;br /&gt;
# You will be greeted by the DACHS cluster, followed by a shell.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
~ $ ssh -l es_vwxyz1234 dachs-login.hs-esslingen.de&lt;br /&gt;
(es_vwxyz1234@dachs-login.hs-esslingen.de) Your OTP: 123456&lt;br /&gt;
(es_vwxyz1234@dachs-login.hs-esslingen.de) Password: &lt;br /&gt;
********************************************************************************&lt;br /&gt;
Last login: Thu Jul  7 18:09:43 2022 from dachs-login.hs-esslingen.de&lt;br /&gt;
********************************************************************************&lt;br /&gt;
[es_vwxyz1234@login1 ~]$ &lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Troubleshooting ==&lt;br /&gt;
&lt;br /&gt;
Nothing yet.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;!-- See [[BwUniCluster_2.0/FAQ#Login_Issues|bwUniCluster FAQ]]. --&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Allowed Activities on Login Nodes =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
To guarantee usability for all the users of clusters you must not run your compute jobs on the login nodes.&lt;br /&gt;
Compute jobs must be submitted to the queuing system.&lt;br /&gt;
Any compute job running on the login nodes will be terminated without any notice.&lt;br /&gt;
Any long-running compilation or any long-running pre- or post-processing of batch jobs must also be submitted to the queuing system.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The login nodes of the DACHS cluster are the access point to the compute system, your &amp;lt;code&amp;gt;$HOME&amp;lt;/code&amp;gt; directory and your workspaces.&lt;br /&gt;
These nodes are shared with all the users therefore, your activities on the login nodes are limited to primarily set up your batch jobs.&lt;br /&gt;
Your activities may also be:&lt;br /&gt;
* &#039;&#039;&#039;short&#039;&#039;&#039; compilation of your program code and&lt;br /&gt;
* &#039;&#039;&#039;short&#039;&#039;&#039; pre- and post-processing of your batch jobs.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;!--&lt;br /&gt;
TODO:&lt;br /&gt;
We advise users to use [[BwUniCluster_2.0_Batch_Queues#Interactive_Jobs|interactive jobs]] for compute and memory intensive tasks like compiling.&lt;br /&gt;
--&amp;gt;&lt;br /&gt;
&lt;br /&gt;
We advise users to use [[DACHS/Queues|interactive jobs]] for compute and memory intensive tasks like compiling.&lt;br /&gt;
&lt;br /&gt;
= Related Information =&lt;br /&gt;
&lt;br /&gt;
* If you want to reset your service password, consult the [[Registration/Password|Password Guide]].&lt;br /&gt;
* If you want to register a new token for the two factor authentication (2FA), consult the [[Registration/2FA|2FA Guide]].&lt;br /&gt;
* If you want to de-register, consult the [[Registration/Deregistration|De-registration Guide]].&lt;br /&gt;
* If you need an SSH key for your workflow, read [[Registration/SSH|Registering SSH Keys with your Cluster]].&lt;br /&gt;
* Configuring your shell: [[.bashrc Do&#039;s and Don&#039;ts]]&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Login&amp;diff=13529</id>
		<title>DACHS/Login</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Login&amp;diff=13529"/>
		<updated>2024-12-19T15:35:21Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: Adjust DNS login host selection&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to DACHS is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All home institutions of our current users are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect to DACHS without restrictions.&lt;br /&gt;
If you are outside one of the BelWü networks (e.g. at home), a VPN connection to the home institution or a connection to an SSH jump host at the home institution must be established first.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The login nodes of the DACHS cluster are the access points to the compute system, your &amp;lt;code&amp;gt;$HOME&amp;lt;/code&amp;gt; directory and your workspaces.&lt;br /&gt;
All users must log in through these nodes to submit jobs to the cluster.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Prerequisites for successful login:&#039;&#039;&#039;&lt;br /&gt;
&lt;br /&gt;
You need to have&lt;br /&gt;
* completed the 3-step [[registration]] procedure.&lt;br /&gt;
* [[Registration/Password|set a service password]] for DACHS.&lt;br /&gt;
* [[Registration/2FA|set up a second factor]] for the time-based one-time password (TOTP).&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login to the DACHS =&lt;br /&gt;
&lt;br /&gt;
Login to the DACHS is only possible with a Secure Shell (SSH) client for which you must know your username on the cluster and the hostname of the login nodes.&lt;br /&gt;
For more general information on SSH clients, visit the [[Registration/Login/Client|SSH clients Guide]].&lt;br /&gt;
&lt;br /&gt;
== Username ==&lt;br /&gt;
&lt;br /&gt;
If you want to use DACHS, you need to add a prefix to your local username: &amp;lt;code&amp;gt;prefix_username&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! University !! Prefix&lt;br /&gt;
|-&lt;br /&gt;
| HS Aalen || aa&lt;br /&gt;
|-&lt;br /&gt;
| HS Albstadt-Sigmaringen || as&lt;br /&gt;
|-&lt;br /&gt;
| HS Esslingen || es&lt;br /&gt;
|-&lt;br /&gt;
| HS Heilbronn || hn&lt;br /&gt;
|-&lt;br /&gt;
| HS Karlsruhe || hk&lt;br /&gt;
|-&lt;br /&gt;
| HTWG Konstanz || ht&lt;br /&gt;
|-&lt;br /&gt;
| HS Mannheim || mn&lt;br /&gt;
|-&lt;br /&gt;
| HS Offenburg || of&lt;br /&gt;
|-&lt;br /&gt;
| HS Reutlingen || hr&lt;br /&gt;
|-&lt;br /&gt;
| HfT-Stuttgart || hs&lt;br /&gt;
|-&lt;br /&gt;
| THU-Ulm || hu&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
For a full list of user names, you can check the [https://www.bwidm.de/hochschulen.php bwIDM Hochschulen page].&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Example:&#039;&#039;&#039;&amp;lt;br/&amp;gt;&lt;br /&gt;
If your local username for the University is &amp;lt;code&amp;gt;vwxyz1234&amp;lt;/code&amp;gt; and you are a user from the University of Esslingen this would combine to: &amp;lt;code&amp;gt;es_vwxyz1234&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
== Hostnames ==&lt;br /&gt;
&lt;br /&gt;
The system has two login nodes.&lt;br /&gt;
The selection of the login node is done automatically.&lt;br /&gt;
If you are logging in multiple times, different sessions might run on different login nodes.&lt;br /&gt;
&lt;br /&gt;
Login to DACHS:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Hostname !! Node type&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login.hs-esslingen.de&#039;&#039;&#039; || login to one of the two login nodes&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
In general, you should use automatic selection to allow us to balance the load over the two login nodes.&lt;br /&gt;
If you need to connect to specific login node, you can use the following hostnames:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Hostname !! Node type&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login1.hs-esslingen.de&#039;&#039;&#039; || DACHS first login node&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login2.hs-esslingen.de&#039;&#039;&#039; || DACHS second login node&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
If you explicitly connect to dachs-login1 but wind up on dachs-login2 (or the other way around), then of of them might not be available at the time and you&#039;re automatically redirected to the other one.&lt;br /&gt;
&lt;br /&gt;
== Host Keys ==&lt;br /&gt;
&lt;br /&gt;
When you log in, you may receive the message &amp;lt;code&amp;gt;The authenticity of host &#039;&amp;lt;host address&amp;gt;&#039; can&#039;t be established.&amp;lt;/code&amp;gt; along with the host key fingerprint. This is intended so you can verify the authenticity of the host you are connecting to. Before you continue you should verify, if this fingerprint matches one of the following:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Algorithm !! Fingerprint (SHA256)&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;RSA&#039;&#039;&#039; || SHA256:kdvbATXbd/ggG33G7VEw+O+FpJPcZU6XDeFyWXvBkhc&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;ECDSA&#039;&#039;&#039; || SHA256:4Y/LvkPL9g9DZ8JrmTxXsMTIWyM/u/mEEmSB7S/2yyA&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;ED25519&#039;&#039;&#039; || SHA256:X9eRJepYD3da3BM1pgiWxnvRc/Pt5eBLUr18tDUsZjU&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Login with SSH command (Linux, Mac, Windows) ==&lt;br /&gt;
&lt;br /&gt;
Most Unix and Unix-like operating systems like Linux, Mac OS and *BSD come with a built-in SSH client provided by the OpenSSH project.&lt;br /&gt;
More recent versions of Windows 10 and Windows 11 using the [https://docs.microsoft.com/en-us/windows/wsl/install Windows Subsystem for Linux] (WSL) also come with a built-in OpenSSH client.&lt;br /&gt;
&lt;br /&gt;
For login use one of the following ssh commands:&lt;br /&gt;
&lt;br /&gt;
 ssh &amp;lt;username&amp;gt;@dachs-login.hs-esslingen.de&lt;br /&gt;
 ssh -l &amp;lt;username&amp;gt; dachs-login.hs-esslingen.de&lt;br /&gt;
&lt;br /&gt;
To run graphical applications, you can use the &amp;lt;code&amp;gt;-X&amp;lt;/code&amp;gt; or &amp;lt;code&amp;gt;-Y&amp;lt;/code&amp;gt; flag to &amp;lt;code&amp;gt;ssh&amp;lt;/code&amp;gt;:&lt;br /&gt;
&lt;br /&gt;
 ssh -Y -l &amp;lt;username&amp;gt; dachs-login.hs-esslingen.de&lt;br /&gt;
&lt;br /&gt;
For better performance, we recommend using [[VNC]].&lt;br /&gt;
&lt;br /&gt;
== Login with graphical SSH client (Windows) ==&lt;br /&gt;
&lt;br /&gt;
For Windows we suggest using MobaXterm for login and file transfer.&lt;br /&gt;
 &lt;br /&gt;
Start &#039;&#039;MobaXterm&#039;&#039;, fill in the following fields:&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
Remote name              : dachs-login.hs-esslingen.de&lt;br /&gt;
Specify user name        : &amp;lt;username&amp;gt;&lt;br /&gt;
Port                     : 22&lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
After that click on &#039;ok&#039;. Then a terminal will be opened and there you can enter your credentials.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; When using File transfer with MobaXterm version 23.6 the following configuration change has to be made:&lt;br /&gt;
In the settings in the tab &amp;quot;SSH&amp;quot;, change the option &amp;quot;SSH engine&amp;quot; from &amp;quot;&amp;lt;new&amp;gt;&amp;quot; to &amp;quot;&amp;lt;legacy&amp;gt;&amp;quot;. Then restart MobaXterm&lt;br /&gt;
&lt;br /&gt;
&amp;lt;!-- TODO: We&#039;ll include this when we got Jupyterhub working.&lt;br /&gt;
&lt;br /&gt;
== Login with Jupyterhub ==&lt;br /&gt;
&lt;br /&gt;
TODO: will there be another URL for this? &lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
Login takes place at:&lt;br /&gt;
* bwUniCluster 2.0: [https://uc2-jupyter.scc.kit.edu uc2-jupyter.scc.kit.edu]&lt;br /&gt;
* SDIL: [https://sdil-jupyter.scc.kit.edu sdil-jupyter.scc.kit.edu]&lt;br /&gt;
&lt;br /&gt;
More Information can be found [[BwUniCluster2.0/Jupyter#Login_process|here]].&lt;br /&gt;
&lt;br /&gt;
--&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Login Example ==&lt;br /&gt;
&lt;br /&gt;
To log in to DACHS, you must provide your [[Registration/Password|service password]].&lt;br /&gt;
Proceed as follows:&lt;br /&gt;
# Use SSH for a login node.&lt;br /&gt;
# The system will ask for a one-time password &amp;lt;code&amp;gt;Your OTP:&amp;lt;/code&amp;gt;. Please enter your OTP and confirm it with Enter/Return. If you do not have a second factor yet, please create one (see [[Registration/2FA]]).&lt;br /&gt;
# The system will ask you for your service password &amp;lt;code&amp;gt;Password:&amp;lt;/code&amp;gt;. Please enter it and confirm it with Enter/Return. If you do not have a service password yet or have forgotten it, please create one (see [[Registration/Password]]).&lt;br /&gt;
# You will be greeted by the DACHS cluster, followed by a shell.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
~ $ ssh -l es_vwxyz1234 dachs-login.hs-esslingen.de&lt;br /&gt;
(es_vwxyz1234@dachs-login.hs-esslingen.de) Your OTP: 123456&lt;br /&gt;
(es_vwxyz1234@dachs-login.hs-esslingen.de) Password: &lt;br /&gt;
********************************************************************************&lt;br /&gt;
Last login: Thu Jul  7 18:09:43 2022 from dachs-login.hs-esslingen.de&lt;br /&gt;
********************************************************************************&lt;br /&gt;
[es_vwxyz1234@login1 ~]$ &lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Troubleshooting ==&lt;br /&gt;
&lt;br /&gt;
Nothing yet.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;!-- See [[BwUniCluster_2.0/FAQ#Login_Issues|bwUniCluster FAQ]]. --&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Allowed Activities on Login Nodes =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
To guarantee usability for all the users of clusters you must not run your compute jobs on the login nodes.&lt;br /&gt;
Compute jobs must be submitted to the queuing system.&lt;br /&gt;
Any compute job running on the login nodes will be terminated without any notice.&lt;br /&gt;
Any long-running compilation or any long-running pre- or post-processing of batch jobs must also be submitted to the queuing system.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The login nodes of the DACHS cluster are the access point to the compute system, your &amp;lt;code&amp;gt;$HOME&amp;lt;/code&amp;gt; directory and your workspaces.&lt;br /&gt;
These nodes are shared with all the users therefore, your activities on the login nodes are limited to primarily set up your batch jobs.&lt;br /&gt;
Your activities may also be:&lt;br /&gt;
* &#039;&#039;&#039;short&#039;&#039;&#039; compilation of your program code and&lt;br /&gt;
* &#039;&#039;&#039;short&#039;&#039;&#039; pre- and post-processing of your batch jobs.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;!--&lt;br /&gt;
TODO:&lt;br /&gt;
We advise users to use [[BwUniCluster_2.0_Batch_Queues#Interactive_Jobs|interactive jobs]] for compute and memory intensive tasks like compiling.&lt;br /&gt;
--&amp;gt;&lt;br /&gt;
&lt;br /&gt;
We advise users to use [[DACHS/Queues|interactive jobs]] for compute and memory intensive tasks like compiling.&lt;br /&gt;
&lt;br /&gt;
= Related Information =&lt;br /&gt;
&lt;br /&gt;
* If you want to reset your service password, consult the [[Registration/Password|Password Guide]].&lt;br /&gt;
* If you want to register a new token for the two factor authentication (2FA), consult the [[Registration/2FA|2FA Guide]].&lt;br /&gt;
* If you want to de-register, consult the [[Registration/Deregistration|De-registration Guide]].&lt;br /&gt;
* If you need an SSH key for your workflow, read [[Registration/SSH|Registering SSH Keys with your Cluster]].&lt;br /&gt;
* Configuring your shell: [[.bashrc Do&#039;s and Don&#039;ts]]&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
	<entry>
		<id>https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Login&amp;diff=13527</id>
		<title>DACHS/Login</title>
		<link rel="alternate" type="text/html" href="https://wiki.bwhpc.de/wiki/index.php?title=DACHS/Login&amp;diff=13527"/>
		<updated>2024-12-19T15:23:12Z</updated>

		<summary type="html">&lt;p&gt;M Kunzelmann: Set host keys&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
Access to DACHS is &#039;&#039;&#039;limited to IP addresses from the BelWü network&#039;&#039;&#039;.&lt;br /&gt;
All home institutions of our current users are connected to BelWü, so if you are on your campus network (e.g. in your office or on the Campus WiFi) you should be able to connect to DACHS without restrictions.&lt;br /&gt;
If you are outside one of the BelWü networks (e.g. at home), a VPN connection to the home institution or a connection to an SSH jump host at the home institution must be established first.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The login nodes of the DACHS cluster are the access points to the compute system, your &amp;lt;code&amp;gt;$HOME&amp;lt;/code&amp;gt; directory and your workspaces.&lt;br /&gt;
All users must log in through these nodes to submit jobs to the cluster.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Prerequisites for successful login:&#039;&#039;&#039;&lt;br /&gt;
&lt;br /&gt;
You need to have&lt;br /&gt;
* completed the 3-step [[registration]] procedure.&lt;br /&gt;
* [[Registration/Password|set a service password]] for DACHS.&lt;br /&gt;
* [[Registration/2FA|set up a second factor]] for the time-based one-time password (TOTP).&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Login to the DACHS =&lt;br /&gt;
&lt;br /&gt;
Login to the DACHS is only possible with a Secure Shell (SSH) client for which you must know your username on the cluster and the hostname of the login nodes.&lt;br /&gt;
For more general information on SSH clients, visit the [[Registration/Login/Client|SSH clients Guide]].&lt;br /&gt;
&lt;br /&gt;
== Username ==&lt;br /&gt;
&lt;br /&gt;
If you want to use DACHS, you need to add a prefix to your local username: &amp;lt;code&amp;gt;prefix_username&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! University !! Prefix&lt;br /&gt;
|-&lt;br /&gt;
| HS Aalen || aa&lt;br /&gt;
|-&lt;br /&gt;
| HS Albstadt-Sigmaringen || as&lt;br /&gt;
|-&lt;br /&gt;
| HS Esslingen || es&lt;br /&gt;
|-&lt;br /&gt;
| HS Heilbronn || hn&lt;br /&gt;
|-&lt;br /&gt;
| HS Karlsruhe || hk&lt;br /&gt;
|-&lt;br /&gt;
| HTWG Konstanz || ht&lt;br /&gt;
|-&lt;br /&gt;
| HS Mannheim || mn&lt;br /&gt;
|-&lt;br /&gt;
| HS Offenburg || of&lt;br /&gt;
|-&lt;br /&gt;
| HS Reutlingen || hr&lt;br /&gt;
|-&lt;br /&gt;
| HfT-Stuttgart || hs&lt;br /&gt;
|-&lt;br /&gt;
| THU-Ulm || hu&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
For a full list of user names, you can check the [https://www.bwidm.de/hochschulen.php bwIDM Hochschulen page].&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Example:&#039;&#039;&#039;&amp;lt;br/&amp;gt;&lt;br /&gt;
If your local username for the University is &amp;lt;code&amp;gt;vwxyz1234&amp;lt;/code&amp;gt; and you are a user from the University of Esslingen this would combine to: &amp;lt;code&amp;gt;es_vwxyz1234&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
== Hostnames ==&lt;br /&gt;
&lt;br /&gt;
The system has two login nodes.&lt;br /&gt;
The selection of the login node is done automatically. (TODO. Needs to be implemented by RZ.)&lt;br /&gt;
If you are logging in multiple times, different sessions might run on different login nodes.&lt;br /&gt;
&lt;br /&gt;
Login to DACHS:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Hostname !! Node type&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login.hs-esslingen.de&#039;&#039;&#039; || login to one of the two login nodes&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
In general, you should use automatic selection to allow us to balance the load over the two login nodes.&lt;br /&gt;
If you need to connect to specific login nodes, you can use the following hostnames:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Hostname !! Node type&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login1.hs-esslingen.de&#039;&#039;&#039; || DACHS first login node&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;dachs-login2.hs-esslingen.de&#039;&#039;&#039; || DACHS second login node&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Host Keys ==&lt;br /&gt;
&lt;br /&gt;
When you log in, you may receive the message &amp;lt;code&amp;gt;The authenticity of host &#039;&amp;lt;host address&amp;gt;&#039; can&#039;t be established.&amp;lt;/code&amp;gt; along with the host key fingerprint. This is intended so you can verify the authenticity of the host you are connecting to. Before you continue you should verify, if this fingerprint matches one of the following:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Algorithm !! Fingerprint (SHA256)&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;RSA&#039;&#039;&#039; || SHA256:kdvbATXbd/ggG33G7VEw+O+FpJPcZU6XDeFyWXvBkhc&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;ECDSA&#039;&#039;&#039; || SHA256:4Y/LvkPL9g9DZ8JrmTxXsMTIWyM/u/mEEmSB7S/2yyA&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;ED25519&#039;&#039;&#039; || SHA256:X9eRJepYD3da3BM1pgiWxnvRc/Pt5eBLUr18tDUsZjU&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Login with SSH command (Linux, Mac, Windows) ==&lt;br /&gt;
&lt;br /&gt;
Most Unix and Unix-like operating systems like Linux, Mac OS and *BSD come with a built-in SSH client provided by the OpenSSH project.&lt;br /&gt;
More recent versions of Windows 10 and Windows 11 using the [https://docs.microsoft.com/en-us/windows/wsl/install Windows Subsystem for Linux] (WSL) also come with a built-in OpenSSH client.&lt;br /&gt;
&lt;br /&gt;
For login use one of the following ssh commands:&lt;br /&gt;
&lt;br /&gt;
 ssh &amp;lt;username&amp;gt;@dachs-login.hs-esslingen.de&lt;br /&gt;
 ssh -l &amp;lt;username&amp;gt; dachs-login.hs-esslingen.de&lt;br /&gt;
&lt;br /&gt;
To run graphical applications, you can use the &amp;lt;code&amp;gt;-X&amp;lt;/code&amp;gt; or &amp;lt;code&amp;gt;-Y&amp;lt;/code&amp;gt; flag to &amp;lt;code&amp;gt;ssh&amp;lt;/code&amp;gt;:&lt;br /&gt;
&lt;br /&gt;
 ssh -Y -l &amp;lt;username&amp;gt; dachs-login.hs-esslingen.de&lt;br /&gt;
&lt;br /&gt;
For better performance, we recommend using [[VNC]].&lt;br /&gt;
&lt;br /&gt;
== Login with graphical SSH client (Windows) ==&lt;br /&gt;
&lt;br /&gt;
For Windows we suggest using MobaXterm for login and file transfer.&lt;br /&gt;
 &lt;br /&gt;
Start &#039;&#039;MobaXterm&#039;&#039;, fill in the following fields:&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
Remote name              : dachs-login.hs-esslingen.de&lt;br /&gt;
Specify user name        : &amp;lt;username&amp;gt;&lt;br /&gt;
Port                     : 22&lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
After that click on &#039;ok&#039;. Then a terminal will be opened and there you can enter your credentials.&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Note:&#039;&#039;&#039; When using File transfer with MobaXterm version 23.6 the following configuration change has to be made:&lt;br /&gt;
In the settings in the tab &amp;quot;SSH&amp;quot;, change the option &amp;quot;SSH engine&amp;quot; from &amp;quot;&amp;lt;new&amp;gt;&amp;quot; to &amp;quot;&amp;lt;legacy&amp;gt;&amp;quot;. Then restart MobaXterm&lt;br /&gt;
&lt;br /&gt;
&amp;lt;!-- TODO: We&#039;ll include this when we got Jupyterhub working.&lt;br /&gt;
&lt;br /&gt;
== Login with Jupyterhub ==&lt;br /&gt;
&lt;br /&gt;
TODO: will there be another URL for this? &lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
Login takes place at:&lt;br /&gt;
* bwUniCluster 2.0: [https://uc2-jupyter.scc.kit.edu uc2-jupyter.scc.kit.edu]&lt;br /&gt;
* SDIL: [https://sdil-jupyter.scc.kit.edu sdil-jupyter.scc.kit.edu]&lt;br /&gt;
&lt;br /&gt;
More Information can be found [[BwUniCluster2.0/Jupyter#Login_process|here]].&lt;br /&gt;
&lt;br /&gt;
--&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Login Example ==&lt;br /&gt;
&lt;br /&gt;
To log in to DACHS, you must provide your [[Registration/Password|service password]].&lt;br /&gt;
Proceed as follows:&lt;br /&gt;
# Use SSH for a login node.&lt;br /&gt;
# The system will ask for a one-time password &amp;lt;code&amp;gt;Your OTP:&amp;lt;/code&amp;gt;. Please enter your OTP and confirm it with Enter/Return. If you do not have a second factor yet, please create one (see [[Registration/2FA]]).&lt;br /&gt;
# The system will ask you for your service password &amp;lt;code&amp;gt;Password:&amp;lt;/code&amp;gt;. Please enter it and confirm it with Enter/Return. If you do not have a service password yet or have forgotten it, please create one (see [[Registration/Password]]).&lt;br /&gt;
# You will be greeted by the DACHS cluster, followed by a shell.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
~ $ ssh -l es_vwxyz1234 dachs-login.hs-esslingen.de&lt;br /&gt;
(es_vwxyz1234@dachs-login.hs-esslingen.de) Your OTP: 123456&lt;br /&gt;
(es_vwxyz1234@dachs-login.hs-esslingen.de) Password: &lt;br /&gt;
********************************************************************************&lt;br /&gt;
Last login: Thu Jul  7 18:09:43 2022 from dachs-login.hs-esslingen.de&lt;br /&gt;
********************************************************************************&lt;br /&gt;
[es_vwxyz1234@login1 ~]$ &lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Troubleshooting ==&lt;br /&gt;
&lt;br /&gt;
Nothing yet.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;!-- See [[BwUniCluster_2.0/FAQ#Login_Issues|bwUniCluster FAQ]]. --&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
= Allowed Activities on Login Nodes =&lt;br /&gt;
&lt;br /&gt;
{|style=&amp;quot;background:#deffee; width:100%;&amp;quot;&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
[[Image:Attention.svg|center|25px]]&lt;br /&gt;
|style=&amp;quot;padding:5px; background:#cef2e0; text-align:left&amp;quot;|&lt;br /&gt;
To guarantee usability for all the users of clusters you must not run your compute jobs on the login nodes.&lt;br /&gt;
Compute jobs must be submitted to the queuing system.&lt;br /&gt;
Any compute job running on the login nodes will be terminated without any notice.&lt;br /&gt;
Any long-running compilation or any long-running pre- or post-processing of batch jobs must also be submitted to the queuing system.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The login nodes of the DACHS cluster are the access point to the compute system, your &amp;lt;code&amp;gt;$HOME&amp;lt;/code&amp;gt; directory and your workspaces.&lt;br /&gt;
These nodes are shared with all the users therefore, your activities on the login nodes are limited to primarily set up your batch jobs.&lt;br /&gt;
Your activities may also be:&lt;br /&gt;
* &#039;&#039;&#039;short&#039;&#039;&#039; compilation of your program code and&lt;br /&gt;
* &#039;&#039;&#039;short&#039;&#039;&#039; pre- and post-processing of your batch jobs.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;!--&lt;br /&gt;
TODO:&lt;br /&gt;
We advise users to use [[BwUniCluster_2.0_Batch_Queues#Interactive_Jobs|interactive jobs]] for compute and memory intensive tasks like compiling.&lt;br /&gt;
--&amp;gt;&lt;br /&gt;
&lt;br /&gt;
We advise users to use [[DACHS/Queues|interactive jobs]] for compute and memory intensive tasks like compiling.&lt;br /&gt;
&lt;br /&gt;
= Related Information =&lt;br /&gt;
&lt;br /&gt;
* If you want to reset your service password, consult the [[Registration/Password|Password Guide]].&lt;br /&gt;
* If you want to register a new token for the two factor authentication (2FA), consult the [[Registration/2FA|2FA Guide]].&lt;br /&gt;
* If you want to de-register, consult the [[Registration/Deregistration|De-registration Guide]].&lt;br /&gt;
* If you need an SSH key for your workflow, read [[Registration/SSH|Registering SSH Keys with your Cluster]].&lt;br /&gt;
* Configuring your shell: [[.bashrc Do&#039;s and Don&#039;ts]]&lt;/div&gt;</summary>
		<author><name>M Kunzelmann</name></author>
	</entry>
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