diff --git a/doc.zih.tu-dresden.de/docs/access/jupyterhub.md b/doc.zih.tu-dresden.de/docs/access/jupyterhub.md
index b5f5df5ebac439f705fd2d639f70022ee25c78ab..639960a5676b464dadbad5475323f358c4c790cc 100644
--- a/doc.zih.tu-dresden.de/docs/access/jupyterhub.md
+++ b/doc.zih.tu-dresden.de/docs/access/jupyterhub.md
@@ -1,7 +1,7 @@
# JupyterHub
With our JupyterHub service we offer you a quick and easy way to
-work with jupyter notebooks on Taurus.
+work with Jupyter notebooks on ZIH systems.
Subpages:
@@ -10,15 +10,15 @@ Subpages:
## Disclaimer
-This service is provided "as-is", use at your own discretion. Please
-understand that JupyterHub is a complex software system of which we are
+This service is provided "as-is", use at your own discretion.
+Please understand that JupyterHub is a complex software system of which we are
not the developers and don't have any downstream support contracts for,
-so we merely offer an installation of it but cannot give extensive
-support in every case.
+so we merely offer an installation of it but cannot give extensive support
+in every case.
## Access
-!!! note
+!!! note
This service is only available for users with an active HPC project.
See [here](../access/overview.md) how to apply for an HPC project.
@@ -26,7 +26,7 @@ JupyterHub is available here: [https://taurus.hrsk.tu-dresden.de/jupyter](https:
## Start a Session
-Start a new session by clicking on the
+Start a new session by clicking on the
button.
@@ -55,13 +55,13 @@ saved in your browser and are lost if you delete your browsing data. Use
the import/export feature (available through the button) to save your
presets in text files.
-!!! info
+!!! info
The [alpha](https://doc.zih.tu-dresden.de/hpc-wiki/bin/view/Compendium/AlphaCentauri)
partition is available only in the extended form.
## Applications
-You can choose between JupyterLab or the classic notebook app.
+You can choose between JupyterLab or classic Jupyter notebooks.
### JupyterLab
@@ -79,7 +79,7 @@ several views:
- details about selected notebook cell
- list of open tabs
-### Classic Notebook
+### Classic Jupyter Notebook
{: align="center"}
@@ -90,10 +90,10 @@ several views:
Initially you will get a list of your home directory. You can open
existing notebooks or files by clicking on them.
-Above the table on the right side is the "New â·" button which lets you
+Above the table on the right side is the button `New` which lets you
create new notebooks, files, directories or terminals.
-## The Notebook
+## Jupyter Notebooks in General
In JupyterHub you can create scripts in notebooks.
Notebooks are programs which are split in multiple logical code blocks.
@@ -119,7 +119,7 @@ tab instead.
{: align="center"}
-**Classic notebook**: Click on the control panel button on the top right
+**Classic Jupyter notebook**: Click on the control panel button on the top right
of your screen.
@@ -131,35 +131,32 @@ Now you are back on the JupyterHub page and you can stop your server by clicking
## Error handling
-We want to explain some errors that you might face sooner or later. If
-you need help open a ticket at HPC support.
+We want to explain some errors that you might face sooner or later.
+If you need help open a ticket at [HPC support](mailto:hpcsupport@zih.tu-dresden.de).
### Error while starting a session
{: align="center"}
-This message often appears instantly if your Slurm parameters are not
-valid. Please check those settings against the available hardware.
+This message often appears instantly if your Slurm parameters are not valid.
+Please check those settings against the available hardware.
Useful pages for valid Slurm parameters:
-- [Slurm batch system (Taurus)] **TODO LINK** (../jobs_and_resources/SystemTaurus#Batch_System)
+- [Slurm batch system (Taurus)](../jobs_and_resources/system_taurus.md#batch-system)
- [General information how to use Slurm](../jobs_and_resources/slurm.md)
### Error message in JupyterLab
-**TODO ADD IMAGE** \<a href="%ATTACHURL%/jupyterlab_error_directory_not_found.png">\<img
-alt="" width="400"
-src="<https://doc.zih.tu-dresden.de/hpc-wiki/pub/Compendium/JupyterHub/jupyterlab_error_directory_not_found.png>"
-style="border: 1px solid #888;" title="Error message: Directory not
-found"/>\</a>
+
+{: align="center"}
If the connection to your notebook server unexpectedly breaks you maybe
will get this error message.
Sometimes your notebook server might hit a Slurm or hardware limit and
gets killed. Then usually the logfile of the corresponding Slurm job
might contain useful information. These logfiles are located in your
-home directory and have the name "jupyter-session-\<jobid>.log".
+home directory and have the name `jupyter-session-<jobid>.log`.
------------------------------------------------------------------------
@@ -172,10 +169,8 @@ Machine Learning Community Edition (formerly
PowerAI)](https://developer.ibm.com/linuxonpower/deep-learning-powerai/)
package suite. You can open a list with all included packages of the
exact standard environment through the spawner form:
-
-**TODO ADD IMAGE** \<img alt="environment_package_list.png"
-src="%ATTACHURL%/environment_package_list.png" style="border: 1px solid
-\#888;" title="JupyterHub environment package list" />
+
+{: align="center"}
This list shows all packages of the currently selected conda
environment. This depends on your settings for partition (cpu
@@ -183,11 +178,11 @@ architecture) and standard environment.
There are three standard environments:
-- production,
-- test,
-- python-env-python3.8.6.
+- production
+- test
+- python-env-python3.8.6
-**Python-env-python3.8.6**virtual environment can be used for all x86
+**Python-env-python3.8.6** virtual environment can be used for all x86
partitions(gpu2, alpha, etc). It gives the opportunity to create a user
kernel with the help of a python environment.
@@ -216,142 +211,111 @@ called kernels.
Creating and using your own kernel has the benefit that you can install
your own preferred python packages and use them in your notebooks.
-We currently have two different architectures at Taurus. Build your
-kernel environment on the **same architecture** that you want to use
+We currently have two different architectures at ZIH systems.
+Build your kernel environment on the **same architecture** that you want to use
later on with the kernel. In the examples below we use the name
"my-kernel" for our user kernel. We recommend to prefix your kernels
-with keywords like "intel", "ibm", "ml", "venv", "conda". This way you
-can later recognize easier how you built the kernel and on which
-hardware it will work.
+with keywords like `haswell`, `ml`, `romeo`, `venv`, `conda`. This way you
+can later recognize easier how you built the kernel and on which hardware it will work.
**Intel nodes** (e.g. haswell, gpu2):
- srun --pty -n 1 -c 2 --mem-per-cpu 2583 -t 08:00:00 bash -l
-
-If you don't need Sandy Bridge support for your kernel you can create
-your kernel on partition 'haswell'.
+```console
+maria@login$ srun --pty --ntasks=1 --cpus-per-task=2 --mem-per-cpu=2541 --time=08:00:00 bash -l
+```
**Power nodes** (ml partition):
- srun --pty -p ml -n 1 -c 2 --mem-per-cpu 5772 -t 08:00:00 bash -l
+```console
+maria@login$ srun --pty --partition=ml --ntasks=1 --cpus-per-task=2 --mem-per-cpu=1443 --time=08:00:00 bash -l
+````
Create a virtual environment in your home directory. You can decide
between python virtualenvs or conda environments.
-<span class="twiki-macro RED"></span> **Note** <span
-class="twiki-macro ENDCOLOR"></span>: Please take in mind that Python
-venv is the preferred way to create a Python virtual environment.
+!!! note
+ Please take in mind that Python venv is the preferred way to create a Python virtual environment.
#### Python virtualenv
-```bash
-$ module load Python/3.8.6-GCCcore-10.2.0
-
-$ mkdir user-kernel #please use Workspaces!
-
-$ cd user-kernel
-
-$ virtualenv --system-site-packages my-kernel
+```console
+marie@compute$ module load Python/3.8.6-GCCcore-10.2.0
+marie@compute$ mkdir user-kernel # please use workspaces!
+marie@compute$ cd user-kernel
+marie@compute$ virtualenv --system-site-packages my-kernel
Using base prefix '/sw/installed/Python/3.6.6-fosscuda-2018b'
New python executable in .../user-kernel/my-kernel/bin/python
Installing setuptools, pip, wheel...done.
-
-$ source my-kernel/bin/activate
-
-(my-kernel) $ pip install ipykernel
+marie@compute$ source my-kernel/bin/activate
+marie@compute$ pip install ipykernel
Collecting ipykernel
-...
+[...]
Successfully installed ... ipykernel-5.1.0 ipython-7.5.0 ...
-
-(my-kernel) $ pip install --upgrade pip
-
-(my-kernel) $ python -m ipykernel install --user --name my-kernel --display-name="my kernel"
+marie@compute$ pip install --upgrade pip
+marie@compute$ python -m ipykernel install --user --name my-kernel --display-name="my kernel"
Installed kernelspec my-kernel in .../.local/share/jupyter/kernels/my-kernel
-
-[now install additional packages for your notebooks]
-
-(my-kernel) $ deactivate
+marie@compute$ pip install [...] # now install additional packages for your notebooks
+marie@compute$ deactivate
```
#### Conda environment
Load the needed module for Intel nodes
-```
-module load Anaconda3
+```console
+marie@compute$ module load Anaconda3
```
... or for IBM nodes (ml partition):
-```
-module load PythonAnaconda
+```console
+marie@ml$ module load PythonAnaconda
```
Continue with environment creation, package installation and kernel
registration:
-```
-$ mkdir user-kernel #please use Workspaces!
-
-$ conda create --prefix /home/<USER>/user-kernel/my-kernel python=3.6
+```console
+marie@compute$ mkdir user-kernel # please use workspaces!
+marie@compute$ conda create --prefix /home/<USER>/user-kernel/my-kernel python=3.6
Collecting package metadata: done
Solving environment: done
[...]
-
-$ conda activate /home/<USER>/user-kernel/my-kernel
-
-$ conda install ipykernel
+marie@compute$ conda activate /home/<USER>/user-kernel/my-kernel
+marie@compute$ conda install ipykernel
Collecting package metadata: done
Solving environment: done
[...]
-
-$ python -m ipykernel install --user --name my-kernel --display-name="my kernel"
+marie@compute$ python -m ipykernel install --user --name my-kernel --display-name="my kernel"
Installed kernelspec my-kernel in [...]
-
-[now install additional packages for your notebooks]
-
-$ conda deactivate
+marie@compute$ conda install [..] # now install additional packages for your notebooks
+marie@compute$ conda deactivate
```
Now you can start a new session and your kernel should be available.
-**In JupyterLab**:
-
-Your kernels are listed on the launcher page:
+**JupyterLab**: Your kernels are listed on the launcher page:
-**TODO ADD IMAGE**\<a href="%ATTACHURL%/user-kernel_in_jupyterlab_launcher.png">\<img
-alt="jupyterlab_app.png" height="410"
-src="<https://doc.zih.tu-dresden.de/hpc-wiki/pub/Compendium/JupyterHub/user-kernel_in_jupyterlab_launcher.png>"
-style="border: 1px solid #888;" title="JupyterLab kernel launcher
-list"/>\</a>
+
+{: align="center"}
You can switch kernels of existing notebooks in the menu:
-**TODO ADD IMAGE** \<a href="%ATTACHURL%/jupyterlab_change_kernel.png">\<img
-alt="jupyterlab_app.png"
-src="<https://doc.zih.tu-dresden.de/hpc-wiki/pub/Compendium/JupyterHub/jupyterlab_change_kernel.png>"
-style="border: 1px solid #888;" title="JupyterLab kernel switch"/>\</a>
-
-**In classic notebook app**:
+
+{: align="center"}
-Your kernel is listed in the New menu:
+**Classic Jupyter notebook**: Your kernel is listed in the New menu:
-**TODO ADD IMAGE** \<a href="%ATTACHURL%/user-kernel_in_jupyter_notebook.png">\<img
-alt="jupyterlab_app.png"
-src="<https://doc.zih.tu-dresden.de/hpc-wiki/pub/Compendium/JupyterHub/user-kernel_in_jupyter_notebook.png>"
-style="border: 1px solid #888;" title="Classic notebook (create notebook
-with new kernel)"/>\</a>
+
+{: align="center"}
You can switch kernels of existing notebooks in the kernel menu:
-**TODO ADD IMAGE** \<a href="%ATTACHURL%/switch_kernel_in_jupyter_notebook.png">\<img
-alt="jupyterlab_app.png"
-src="<https://doc.zih.tu-dresden.de/hpc-wiki/pub/Compendium/JupyterHub/switch_kernel_in_jupyter_notebook.png>"
-style="border: 1px solid #888;" title="Classic notebook (kernel
-switch)"/>\</a>
+
+{: align="center"}
-**Note**: Both python venv and conda virtual environments will be
-mention in the same list.
+!!! note
+ Both python venv and conda virtual environments will be mention in the same list.
### Loading modules
diff --git a/Compendium_attachments/JupyterHub/switch_kernel_in_jupyter_notebook.png b/doc.zih.tu-dresden.de/docs/access/misc/jupyter_notebook_change_kernel.png
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