How to use GPUs

If you think your work would benefit from use of GPUs, there are several options available to you:

1, Sign up for an HPC (High Performance Computing) account here [1]. All members of the University may apply for a free service level 3 account. Additionally the Department has made some funds available for use of the higher-priority service level 2. See this page for info [2]. Or, check with your project supervisor whether there are any grant-specific funds available for paid use of the HPC. Allow a week for your application to be approved (often it's faster). Once signed up, check out the documentation [3] and note that use of the HPC is charged per hour per core, so use it with care! Also be sure that you need to use GPU: it may be that the CPU services offered by the HPC will be sufficient for your needs. As a few starter tips (for detail see the current documentation): you specify in your log-in host address whether you want to use CPU or GPU, you'll likely need to load software-specific modules into your environment to get started, there are example batch submission scripts for you to modify in /usr/local/Cluster-Docs/SLURM, and if you're on a paying tier you can check the balance on the account you're using with the "gbalance -p <account_name>" command.

2, Ask sys-admin if you can have access to a virtual machine running on the Department's GPUs. This is primarily intended for MPhil students. More info here [4].

3, Check with your supervisor / others in your group: has your group bought its own GPUs? You might be granted access to them if so.

4. PIs might also be interested in HPC services available outside Cambridge: for instance by application to the EPSRC [5] or the Oxford-based JADE facility [6].

This wiki page was put together by Andrew Caines (apc38) thanks to help from Daniel Bates, Chris Hadley, Markus Kuhn, Graham Titmus, Aaron Zhao and Noa Zilberman. Any errors are my own: feel free to send me feedback or add your own hints and tips on GPU use.

If you have questions, there's also a mailing list for GPU users in the department. You can find the archives and manage your subscription here [7].