Fair Use Policy

GPULab jobs are subject to a fair usage policy to ensure that the GPULab resources are used fairly and efficiently.

General rules

• Jobs must only request required resources. Wasting GPULab resources may result in your jobs being cancelled and future jobs being deprioritized.
• Jobs must be relevant to the project in which they are being run. Request a new project if necessary.

Good practices

• Jobs should start their computation automatically, without the need of manual intervention.
• When multiple GPU’s are requested, the amount of non-GPU preprocessing should be minimized: computations on the GPU should have start within the first hour after the job started running.
• Jobs should stop to release the allocated resources once the computation has ended.
• Long running jobs should checkpoint their computations: hardware failures do occur, make sure that you don’t lose days worth of work.
• Split your work into multiple smaller jobs: this allows them to run in parallel and reduces job run time.