Someone else may see another option, but NVIDIA MIG seems like the straightforward option. That would require both a Slurm upgrade and the purchase of MIG-capable cards.
https://slurm.schedmd.com/gres.html#MIG_Management Would be able to host 7 users per A100 card, IIRC. On Apr 3, 2022, at 4:20 PM, Kamil Wilczek <km...@mimuw.edu.pl> wrote: Hello! I am an administrator of a GPU cluster (Slurm version 19.05.5). Could someone help me a little bit and explain if a single GPU can be shared between multiple users? My experience and documentation tells me that it is not possible. But even after some time Slurm is still a beast to me and I find myself struggling :) * I setup the cluster to assign GPUs on multi-GPU servers to different users using GRES. This works fine and several users can work on a multi-GPU machine (--gres=gpu:N/--gpu:N). * But sometimes I have requests to allow a group of students to work simultaneously, interactively on a small partition, where there is more users than GPUs. So I thought that maybe an MPS is a solutions, but the docs says that MPS is a way to run multiple jobs of *the same* user on a single GPU. When another user is requesting a GPU by MPS, the job is enqueued and waiting for the first users' MPS server to finish. So, this is not a solution for a multi-user, simultaneous/parallel environment, right? Is there a way to share a GPU between multiple users? The requirement is, say: * 16 users working interactively, simultaneously * 4 GPUs partition Kind Regards -- Kamil Wilczek [https://keys.openpgp.org/] [D415917E84B8DA5A60E853B6E676ED061316B69B]
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