For TAs

We are building up the necessary tools to allow TAs to grant more time and have control over the resources of a course. Once this toolkit is available the documentation will go here.

What to Tell Your Students

Please give the following information to students of a course (if relevant):

  • For JupyterHub:
    • Details about the environment(s) under /cluster/courses that you have enabled in the hub.
  • For running jobs:
    • The course tag.
    • The maximum job duration.
    • If jobs are preempted or not. If they are students must account for more time until they get the result.
    • Paths to any prepared environment or installed software under /cluster/courses and how to use it.

Students also need to know that the cluster resources should only be used for the course. If students runs out of GPU time for a course they need to contact a TA. TAs can ask our service desk to increase time for given students.

Preempted Jobs

Long running jobs can be canceled by more important jobs if the cluster is full. These jobs will automatically restart when there are enough nodes free again.

To avoid running the whole job from the beginning students need to know techniques to use checkpoints or save state in order to resume from somewhere shortly before the job was killed.


Please tell your students to use the --no-cache-dir option when using pip. Alternatively pip cache purge can be used to clear the cache after installation.

For Anaconda there is not way to avoid the cache but with conda clean --all the cache space can be freed.

If you provide scripts to your students then please integrate the above to save space in the home directories.

Sharing Data with Students

You can create a folder

/cluster/courses/{course tag}/data_for_users

which will be automatically linked as {course tag}_data into the home/work directory of any user that logs in to a login node or starts a Jupyter notebook for your course. Examples, templates and solutions can be placed there for all of your participants. Only participants and TAs of the course can access the data. The data will be read only - participants can copy data such as Jupyter notebooks into their home directory from there to alter them.

By default all files in the data_for_users folder are readable by the participants of the course. Be careful what you put there and when.

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