JupyterHub on the Teach Cluster

JupyterHub provides students access to Jupyter notebooks with the capability of connecting to dedicated computing resources on the Teach Cluster. Through this webportal, students can request access to CPU and GPU compute nodes for classwork.

Step 1. Connecting to JupyterHub

Point your browser to the address below and authenticate using your Pitt credentials. The username needs to be all lowercase and is the same one used to access my.pitt.edu. The web host should be accessible for all users while connected through Wireless-PittNet. If that is not the case, please try again while on VPN.

Step 2. Configuring Jupyterhub session

After logging in, you will be presented by the JupyterHub configuration page which looks like the image below. The Select Partition dropdown menu provides 4 preset configurations on the TEACH cluster. The configurations are as follows:

  • Teach - 6 CPUs - 45GB
  • Teach - Nvidia GTX 1080 GPU - 2 CPUs - 20GB
  • Teach - Nvidia Titan X GPU - 3 CPUs - 24GB
  • Teach - Nvidia L4 GPU - 16 CPUs - 60GB

The 4 configurations are designed to best utilize the available resources on the TEACH cluster. All of them are configured to run for 3 hours.

The Select Virtual Environment dropdown menu allows you to select the Python environment you want to use. The default is the base environment, which is a standard Python 3.11 installation. If your class needs a specific Python environment, please submit a help ticket and we will create it for you, so you can select it from the dropdown menu. The menu also includes a Provide custom path option which allows you to specify a custom Python environment path. Please refer to the Create a virtual environment for JupyterHub Article for more instructions on how to create a custom Python environment for JupyterHub.

Pressing Start will launch the job to the Teach Cluster and send back a Jupyter Notebook on the web GUI.

You can use the Account field to specify a different SLURM account to use for the session other than your default account, for example, if you are part of a research group with a SLURM account called panthers and it's your default SLURM association; however, you will be using JupyterHub for a class that has a SLURM account called datasci, you can specify datasci in the Account field. If you leave it blank, your default SLURM account will be used.

Step 3. Interacting with the Jupyter Notebook

If you encounter success, you will see the GUI below. The Project Jupyter site has good documentation on all aspects of the GUI.

Should you be unsuccessful in getting a Jupyter Notebook instance, please submit a help ticket and we will troubleshoot. A potential error could be that your account does not have an allocation on the Teach Cluster. A symptom of this error is shown in the Appendix at the bottom.

Step 4. Ending session

Be sure to save all your work before ending your session.

Select the Hub Control Panel to bring up the option to stop the server.

Appendix: Errors

Your request for a Jupyter Notebook on the Teach Cluster will fail if your account does not have an allocation there. The error may manifest as shown below.