Page Comparison

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You have the possibility of creating a preset with predefined start options for yourself or your project group.

Note: The preset functionality is currently only available on Noctua 2.

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Click here to list your presets: https://jh.pc2.uni-paderborn.de/services/presets/

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When you click on the tile ‘Xpra Desktop’, a remote desktop environment is set up in the background. Graphical applications (e.g. loaded via modules) can be started from the started graphical terminal.

How-To

Creating presets

Note: The preset functionality is currently only available on Noctua 2.

To save time when configuring your Jupyter environenment you have the possibilty to create preset environments for yourself or your compute time group(s).

Created presets can be selected when starting a new Jupyter instance:

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Create presets here: https://jh.pc2.uni-paderborn.de/services/presets/ (or JupyterHub home → services → presets)

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Spawner

• Local spawner (on JupyterHub)

  • Spawning the Jupyter notebook environment on the JupyterHub host. Slurm job flags not needed.

    • Slurm tools, Modules, Remote desktop environment are available.

• Noctua 2 (via Slurm)

  • Spawning the Jupyter environment inside a Slurm job (on a compute/gpu/fpga node) on Noctua 2. Note: You need to specifiy Slurm job flags.

Preset scopes

Select who can use your preset. You or one of your compute time projects.

Default URL

The URL to which JupyterHub redirects when the server is started.

Example:

/lab -> Spawning JupyterLab environment

/xprahtml5 -> Spawning Remote desktop environment

Notebook directory

The working directory. Used for JupyterLab, the remote desktop environment and the classic Jupyter view.

Apptainer container

Your self-built Apptainer/Singularity container. Have a look here for creating your own container: https://upb-pc2.atlassian.net/wiki/spaces/PC2DOK/pages/1903131/JupyterHub#Create-my-own-Apptainer%2FSingularity-container

Environment variables

Extra environment variables.

Format:

MY_ENV_VAR=”Hello World”
FOO=BAR

Modules

Extra Lmod modules to load on start time. All system modules and Jupyter specific kernels are available.

Slurm job flags

Slurm job flags in Slurm batch format. Example:

#SBATCH --partition=normal
#SBATCH --time=01:00:00

Create custom IPython kernel inside custom conda environment

1. Create a conda environment as described here:

   1. Python & Python Package Management

2. conda activate <your_conda_env>

3. conda install ipykernel

   1. Or: python3 -m pip install ipykernel

4. ipykernel install --user --name <KERNELNAME> --display-name "<DISPLAY NAME>"

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apt -y install lua5.3 lua-posix

mkdir -p /usr/lib64/lua/5.3
cp /usr/lib/x86_64-linux-gnu/liblua5.3-posix.so.1 /lib64/lua/5.3/
mv /lib64/lua/5.3/liblua5.3-posix.so.1 /lib64/lua/5.3/posix.so

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Make Slurm Tools inside my container available

groupadd --gid 351 munge
groupadd --gid 567 slurm
useradd -d /var/run/munge -M --gid 351 --uid 994 --shell /sbin/nologin munge
useradd -d /opt/software/slurm -M --gid 567 --uid 567 --shell /bin/false slurm

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ln -s /scratch/hpc-prf-project/jupyter_container.sif $HOME/.jupyter/pc2-jupyterhub/

Access remote JupyterHub server with the local Visual Studio Code instance

You need following extensions for Visual Studio Code:

• https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter

• https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter-hub

1. Create an acccess token in the JupyterHub web interface:

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2. Follow following instructions described here: https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter-hub

   1. You need to start a Jupyter session using our JupyterHub web interface. After successful start, you can copy the URL starting with https://jh.pc2.uni-paderborn.de/user/.../...

View Slurm job logs

If the path of the Slurm Job output has not been changed explicity, it can be found here by default:

Noctua 1: $HOME/.jupyter/last_jh_noctua1.log

Noctua 2: $HOME/.jupyter/last_jh_noctua2.log

PC² Support

If you have any other problems that won’t be solved, please contact the pc2-support@uni-paderborn.de

Troubleshooting

JupyterLab

“A Jupyter server is running.” message

• This message appears because user settings managed by JupyterLab do not match the new JupyterLab version.

  • Try deleting ~/.jupyter/ in your $HOME directory as follows:

    • rm -r ~/.jupyter/

  • If you want to keep your custom user settings, write an email to pc2-support@uni-paderborn.de