I am imagine part of the reason is to keep people from running CPU jobs that would take more than 20 cores on the GPU machine as others do not have GPU's. I'd be interested in knowing strategies here too.
____ *Note: UMDNJ is now Rutgers-Biomedical and Health Sciences* || \\UTGERS |---------------------*O*--------------------- ||_// Biomedical | Ryan Novosielski - Senior Technologist || \\ and Health | [email protected]<mailto:[email protected]>- 973/972.0922 (2x0922) || \\ Sciences | OIRT/High Perf & Res Comp - MSB C630, Newark `' On Apr 6, 2015, at 20:17, Ryan Cox <[email protected]<mailto:[email protected]>> wrote: Chris, Just have GPU users request the numbers of CPU cores that they need and don't lie to Slurm about the number of cores. If a GPU user needs 4 cores and 4 GPUs, have them request that. That leaves 20 cores for others to use. Ryan On 04/06/2015 03:43 PM, Christopher B Coffey wrote: Hello, I’m curious how you handle the allocation of GPU’s and cores on GPU systems in your cluster. My new GPU system is 24 core, with 2 Tesla K80’s (4 gpus total). We allocate cores/mem by: SelectType=select/cons_res SelectTypeParameters=CR_Core_Memory What I’m thinking of doing is lying to Slurm about the true cores, and specifying CPUs=20, along with Gres=gpu:tesla:4. Is this a reasonable solution in order to ensure there is a core reserved for each gpu in the system? My thought is to allocate the 20 cores on the system to non-GPU type work instead of leaving them idle. Thanks! Chris
