Agree with that. Plus, of course, even if the jobs run a bit slower by not
having all the cores on a single node, they will be scheduled sooner, so the
overall turnaround time for the user will be better, and ultimately that's what
they care about. I've always been of the view, for any scheduler, that the
less you try to constrain it the better. It really depends on what you're
trying to optimise for, but generally speaking I try to optimise for maximum
utilisation and throughput, unless I have a specific business case that needs
to prioritise particular workloads, and then I'll compromise on throughput to
get the urgent workload through sooner.
Tun
________________________________
From: Loris Bennett via slurm-users <slurm-users@lists.schedmd.com>
Sent: 09 April 2024 06:51
To: slurm-users@lists.schedmd.com <slurm-users@lists.schedmd.com>
Cc: Gerhard Strangar <g...@arcor.de>
Subject: [slurm-users] Re: Avoiding fragmentation
Hi Gerhard,
Gerhard Strangar via slurm-users <slurm-users@lists.schedmd.com> writes:
> Hi,
>
> I'm trying to figure out how to deal with a mix of few- and many-cpu
> jobs. By that I mean most jobs use 128 cpus, but sometimes there are
> jobs with only 16. As soon as that job with only 16 is running, the
> scheduler splits the next 128 cpu jobs into 96+16 each, instead of
> assigning a full 128 cpu node to them. Is there a way for the
> administrator to achieve preferring full nodes?
> The existence of pack_serial_at_end makes me believe there is not,
> because that basically is what I needed, apart from my serial jobs using
> 16 cpus instead of 1.
>
> Gerhard
This may well not be relevant for your case, but we actively discourage
the use of full nodes for the following reasons:
- When the cluster is full, which is most of the time, MPI jobs in
general will start much faster if they don't specify the number of
nodes and certainly don't request full nodes. The overhead due to
the jobs being scattered across nodes is often much lower than the
additional waiting time incurred by requesting whole nodes.
- When all the cores of a node are requested, all the memory of the
node becomes unavailable to other jobs, regardless of how much
memory is requested or indeed how much is actually used. This holds
up jobs with low CPU but high memory requirements and thus reduces
the total throughput of the system.
These factors are important for us because we have a large number of
single core jobs and almost all the users, whether doing MPI or not,
significantly overestimate the memory requirements of their jobs.
Cheers,
Loris
--
Dr. Loris Bennett (Herr/Mr)
FUB-IT (ex-ZEDAT), Freie Universität Berlin
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