JupyterHub

If you are looking for a convenient way to run JupyterLab notebooks try UFRC JupyterHub service. It presents a convenient web interface to start notebooks, consoles, or terminals with multiple custom kernels and several job resource request profiles, which we can expand on request to satisfy your needs.

Jupyter Notebooks are only accessible from within the UF network. Use the VPN if off campus.

You might see a different username in the top-right corner of your JHub page. This is a mostly harmless caching issue, a trade-off for performance.

• The main user impact is that if this occurs, you will need to force a reload of the page to stop your server.
  • To force a hard reload of the JHub webpage: use shift+F5 or hold the shift key on the keyboard and click on the reload browser button)
  • After a reload, you will see your username in the top-right corner and be able to stop your server

This is a known issue. We will update JHub when there is a fix.

Connect to https://jupyterhub.rc.ufl.edu

• Using your web browser navigate to https://jupyterhub.rc.ufl.edu and login with your GatorLink credentials.

Select the Desired Resources from the Dropdown

JupyterHub can only use resources from your primary group's allocation. If you need yo use resources from a secondary group, please use Jupyter via Open on Demand.

• 
  The dropdown menu lists the available job profile options for the resource request for your Jupyter Server. As with all jobs run through the scheduler, these resources are the number of CPU cores, amount of memory (RAM), number of GPUs and the time these resources are allocated for.
• Be sure to select reasonable resources for the work you plan to do and the allocation your group has. Once allocated to your job, those resources are unavailable to other users in your group for the duration of your job.

Remember that leaving idle Jupyter servers running wastes resources and prevents you and others from using those resources. See below of information on how to stop your server when you are done working.

• After selecting the profile you want to use, click the start button.

• After clicking Start, your job is submitted to the SLURM scheduler requesting the resources indicated. It may take a few minutes or longer for your job to start depending on cluster load and your group's available resources.

Stopping Your Server When Finished

If you are done with your work, rather than leaving the server running with idle resources tied up with your job, please stop your server.

• From the File menu, select Hub Control Panel
• As noted above, there is a caching bug in JupyterHub that may result in you having a different user's GatorLink in the top right of the page. If that is the case, do a hard refresh of the page.

• After verifying your username, click the Stop My Server button.

Video Summary of Running Jupyter Notebooks on HiPerGator

[8 min, 1 sec] This video covers the use of Jupyter Notebooks via https://jhub.rc.ufl.edu/ to run Python, R and other notebooks on HiPerGator.

• Connect to https://jhub.rc.ufl.edu/
• Launch notebooks in various coding languages
• Launch a terminal
• Upload and download files via your browser

Available Kernels

• 'Python3 3.7 (basic)' - the default python3 kernel from the jupyterhub, which doesn't have much in it.
• 'Python3 3.6 (full)' - our main HiPerGator python3/3.6 environment module with "Everything and the kitchen sink" in it as far as python modules are concerned.
• 'PyViz-0.10.0' - special environment for https://pyviz.org/ based data analysis and plotting environment.
• 'R 3.6 (full)' - our main R/3.6 environment module from HiPerGator with everything and a kitchen sink as far as packages are concerned.

Packages and modules in the full python3 and R environments are installed on request (https://support.rc.ufl.edu).

Users can define their own Jupyter kernels for use in JupyterHub. See https://jupyter-client.readthedocs.io/en/stable/kernels.html

In short, kernel definitions can be put into ~/.local/share/jupyter/kernels directory. See /apps/jupyterhub/kernels/ for examples of how we define commonly used kernels.