DACHS/Jupyter

Short description of Jupyter

Jupyter (an acronym for Julia, Python and R) 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'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.

We provide JupyterHub at https://dachs-jupyter.hs-esslingen.de/ as described below.

Access requirements

Access to Jupyter is limited to IP addresses from the BelWü network. 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's VPN, and not in SPLIT tunneling mode, see Login page.

Prerequisites

1. Register as described on the Registration
2. Then login to DACHS via SSH at least once: This ensures that your home directory is setup properly on DACHS
3. Make sure you're connected to the VPN of your university (see above)

Login process

After having logged into

 https://dachs-jupyter.hs-esslingen.de

You will need to specify the resources, as described in the next section.

Selection of Compute Resources

After you logged in via bwIDM, you can select the resources for your Jupyter Notebook.

Preselected are the following values, but you can adjust them as needed:

• 1 CPU core
• 16 GB of RAM
• No GPU
• Job runtime of 30 minutes
• Load the jupyter/ai module (a virtual environment containing libraries typically needed for machine learning)
• Use the default JupyterHub reservation. From Monday to Friday, from 08:00 to 20:00 o'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.

When you adjusted your resources, press start and the Notebook is started for you.

If you want to use a custom reservation, for example a reservation you previously requests, then un-check the box after Use default reservation and enter your custom reservation name and the token that you received from us.

Request a Reservation for Your Lecture

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. Furthermore, it's easy:

1. Send an email with the following information:

• Start time and duration
• How many nodes do you request? Generally, we assign nodes from the gpu1 partition to JupyterHub jobs.
• Do you request a one-time or periodic reservation?
• The usernames that should have access to the reservation. This is at least your username. (For example es_username). 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.

2. Wait for a reply. You'll get a reservation name and a reservation token that must be entered in the resource selection dialog of JupyterHub.