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PC² JupyterHub

The JupyterHub service is available for Noctua 1 and Noctua 2.

Access

The JupyterHub can be reached at the following address:

Noctua 2: https://jh.pc2.uni-paderborn.de

Noctua 1: https://jh.noctua1.pc2.uni-paderborn.de

The JupyterHub can be accessed via VPN or on-site at the University of Paderborn.

image-20240422-114054.png

Quick Start

Spawn host/resources

Start

Jupyter Session on Noctua 2

Quick Start

Jupyter Session on Noctua 1

Quick Start

Jupyter Notebook on Noctua 2

(Inside Slurm job, 1h runtime, normal partition)

Quick Start

Jupyter Notebook on Noctua 2

(Inside Slurm job, 1h runtime, gpu partition)

Quick Start

Jupyter Notebook on Noctua 1

(Inside Slurm job, 1h runtime, normal partition)

Quick Start

Jupyter Notebook on Noctua 1

(Inside Slurm job, 1h runtime, gpu partition - 1x A40)

Quick Start

Server Options

Presets

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

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

Simple

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Preset enviroments with predefined values how to start the Jupyter Notebook.

Default and self-created apptainer containers can be used.

Advanced (Slurm)

An advanced view with setting options how a Slurm job should be startet on a cluster.

Loading additional Jupyter kernels

You can load additional Jupyter kernel using Lmod (module). Following kernel are currently available:

image-20240422-115034.png

If you need new kernel versions or even other programming languages then you are welcome to contact pc2-support!

Apptainer (Singularity) Container

In JupyterHub it is possible to launch Jupyter Notebook instances inside a Singularity container. This has the advantage of being able to use your own built environment. When starting a container, any directories can be mounted inside the container environment.

We provide a set of default Singularity containers:

Container name

Kernels available

Installed software

jupyter_scientific_python

Python

jupyter_datascience

Julia, Python, R

  • All from “jupyter_scientifc_python”

  • rpy2 package

  • The Julia compiler and base environment

  • IJulia to support Julia code in Jupyter notebooks

  • HDF5, Gadfly, RDatasets packages

To learn more about Singularity, see here: Singularity-Introduction

If you want to build your own Singularity container for JupyterHub, see here: Create my own Singularity container

Remote Desktop (Graphical Environment via Xpra)

To create a remote desktop environment, you can click on "Desktop Environment" in the JupyterLab interface:

image-20240422-114609.png

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

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

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

Loading software modules using JupyterLab

To load software modules inside JupyterLab, click on the Lmod extension tab. Then you have the possibility to search, load and unload modules.

If you are using the Classic Notebook View, click on tab "Softwares" to load software modules.

Create my own Singularity container

Installing Jupyter tools

You do not need to install the Jupyter client tools inside your Singularity container.

If the file /opt/conda/bin/jupyterhub-singleuser does not exists inside your container, the JupyterHub binds its own tools inside your container at run time.

If you want to manage your own Jupyter tools/extensions please make sure /opt/conda/bin/jupyterhub-singleuser exists inside your Singularity container.

Using Docker stacks

It is possible to build singularity containers from the official jupyter docker stacks:

https://jupyter-docker-stacks.readthedocs.io/en/latest/

Here are more information on how to build a singularity container from DockerHub:

https://sylabs.io/guides/3.7/user-guide/build_a_container.html

Container Location

Your new created container can only be placed in your $HOME directory: $HOME/.jupyter/pc2-jupyterhub/

Alternatively you can create a link from your $PC2PFS to your $HOME directory:

$ ls -l /scratch/pc2-mitarbeiter/mawi/jupyter_container.sif
  -rw-r--r--. 1 mawi pc2-mitarbeiter 0 Dec 17 07:53 /scratch/pc2-mitarbeiter/mawi/jupyter_container.sif
$ ln -s /scratch/pc2-mitarbeiter/mawi/jupyter_container.sif $HOME/.jupyter/pc2-jupyterhub/

All containers with type .sif will be automatically detected in $HOME/.jupyter/pc2-jupyterhub/

Troubleshooting

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

“Terminals unavailable”

If you have terminado installed in your $HOME directory (pip3 install --user), please make sure that the version of terminado is at least 0.8.3.

PC² Support

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

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