Priority algorithms and resource limits have their limitations. Sharing computational resources requires every user to play nice and fair. Be mindful of the fact that other students are using the system and on a typical semester – hundreds students may have permissions on every cluster at a time.
Please follow these guidelines so that everyone can have a positive experience:

  • Don’t abuse the queue: Even if there are no limits on the number of jobs you can queue, don’t overflow it.
  • Don’t abuse loopholes: No system is perfect and no system is watertight. If you find a scenario on which you can bypass job, resource or queue limits – please report.
  • Close idle jobs: The system cannot tell if you’re currently in front of your PC or just left Jupyter Notebook open and went to sleep – these resources could be used by someone else.
  • Don’t overschedule resources: If you need just one GPU – ask for one GPU. Hogging resources needlessly affects everyone – including you, when calculating priority for future jobs.
  • Prefer small jobs over one massive script: If you can modulate your work – please do. This helps for better job scheduling as well as protects against jobs fails.
  • Be nice: Your work is as important for you as everyone else’s work for them. Use common sense when sending jobs.
  • Don’t wait until the last minute: The cluster tends to be flooded with jobs on the week before a submission deadline. Take that into account when managing your time.
  • Understand workload management: The cluster promises to run every job at a reasonable time – it does not promise to run your job RIGHT NOW. Again: Manage your time accordingly.
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