Jupyter OOD

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Launching a JupyterLab server via Open on Demand

Open on Demand is only accessible from the UF network. Use the VPN if off campus.

Open on Demand is a service that provides web-based access to HiPerGator, including Jupyter Lab and Jupyter Notebooks.

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

  • Using your web browser navigate to https://ood.rc.ufl.edu/ and login with your GatorLink credentials.
  • See the Open on Demand for information on file management, shell access and other features available from Open on Demand.

Select Jupyter Notebook from the interactive Apps Menu and fill out form

  • From the Interactive Apps menu, select Jupyter Notebook from the Servers section of the menu near the bottom. OOD JupyterServer.png
  • The next page presents a form with many options for scheduling your job.
OOD SLURM options 01.png
  • Settings of particular importance:
    • Number of CPU cores requested per MPI task (--cpus-per-task, -p): How many CPU cores do you want? Most Python Notebooks will only use a single CPU core, so requesting more is generally not needed. If you are using multiple cores, set the number here.
    • Maximum memory requested for this job in Gigabytes (--mem, -m): How much memory should be allocated to your job. This should be a reasonable estimate of the amount of memory (RAM) that you will use during your session in GB. If you experience Jupyter Kernels dying while running your notebooks, this may be an indication of not having enough memory. Restarting a session with more RAM may help.
    • SLURM Account (--account, -A) and QoS (Required if custom Account is set, --qos, -q): Account and QOS can be set to use a secondary group (such as a course allocation). Most users will not need to change these settings.
      OOD.account qos.screenshot.png
    • Time Requested for this job in hours (--time, -t): How long your Jupyter server should run for.
      Remember that leaving idle Jupyter servers running wastes resources and prevents you and others from using those resources. This time should be set to the amount of time you will be actively working and running analyses.
    • Cluster partition (--partition, -p): Leave as default unless are requesting a GPU or have a specific reason to select a partition.
    • Generic Resource Request (--gres): If you are requesting a GPU, add the information here using the GPU Access page as a guide.

Once you have used Open On Demand once, your settings will typically be saved for future sessions. If you run similar sessions, you can scroll to the bottom and click Launch.

Wait for job to start and then connect

  • After clicking Launch, your job will be submitted to the SLURM scheduler requesting the resources you have selected. At first the job will be listed with the image below. Remember that resources are allocated to groups based on investment, other jobs using the group's resource may delay the start of your job.
OOD Queued.png
  • Once your job starts the Connect button will appear. Click that to connect to your Jupyter session.
OOD Running.png

Reconnecting to Running Sessions

You can close your browser window and reconnect to existing sessions using the My Interactive Sessions menu (sometimes shown with just the icon on smaller screens).

OOD MyInteractiveSessions.png

Deleting Running Sessions

Your Jupyter session will run for the time you selected, consuming the allocated resources. If you are finished with your analyses, you can release those resources by deleting the job. Using the My Interactive Sessions menu shown above, find the session and click the Delete button. The Delete button stops the SLURM job. The Notebooks/files/etc. created in your job are not deleted.

OOD Running.png

Using the Older Jupyter Notebook Interface

OOD Jupyter SimpleNotebooks.png

By default, the checkbox show at the right is selected, starting your server with the more modern JupyterLab interface. If you want to use the older, simpler Jupyter Notebook interface uncheck the box.