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Jupyter via Open OnDemand

Open OnDemand presents another method to start a JupyterLab server that offers additional resource and account selection options beyond the dropdown available in JupyterHub. JupyterLab via OOD allows user configurable resource requests, group selection and other options.

Note

Notebooks running in the GPU partition are limited to 72 hours of runtime.

Connect to Open OnDemand

Start a Jupyter Notebook Interactive App

  • From the Interactive Apps menu, select Jupyter Notebook in the Servers section of the menu near the bottom. 150px
  • The next page presents a form with many options for scheduling your job. 300px
  • 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. 300px|frameless|right
  • 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 OnDemand once, your settings will typically be saved for future sessions. If you run similar sessions, you can scroll to the bottom and click Launch.

Job Start and Connect

  • After clicking on the Launch button 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. 400px|center
  • Once your job starts the Connect button will appear. Click that to connect to your Jupyter session.

Reconnecting to Running Sessions

right 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).

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.

Filesystem Access

See Jupyter Filesystem Access for details on how to set up convenient filesystem access from the jupyterlab interface.