Hi all, I'm curious to know what/how/where/if sites do to try and reduce the impact of fragmentation of resources by small/narrow jobs on systems where you also have to cope with large/wide parallel jobs?
For my purposes a small/narrow job is anything that will fit on one node (whether a single core job, multi-threaded or MPI). One thing we're considering is to use overlapping partitions in Slurm to have a subset of nodes that are available to these types of jobs and then have large parallel jobs use a partition that can access any node. This has the added benefit of letting us set a higher priority on that partition to let Slurm try and place those jobs first, before smaller ones. We're already using a similar scheme for GPU jobs where they get put into a partition that can access all 36 cores on a node whereas non-GPU jobs get put into a partition that can only access 32 cores on a node, so effectively we reserve 4 cores a node for GPU jobs. But really I'm curious to know what people do about this, or do you not worry about it at all and just let the scheduler do its best? All the best, Chris -- Chris Samuel : http://www.csamuel.org/ : Melbourne, VIC _______________________________________________ Beowulf mailing list, Beowulf@beowulf.org sponsored by Penguin Computing To change your subscription (digest mode or unsubscribe) visit http://www.beowulf.org/mailman/listinfo/beowulf