It sounds like you really want/need oversubscribe to be off.
That being said, perhaps you could do a combo of exclusive and mem=0. The mem=0 should still allocate all the memory (thus the entire node) and the exclusive will allow the job to access all the cpus/cores/gpus.
Brian Andrus
On 3/30/2026 8:46 AM, Dustin Lang via slurm-users wrote:
Hi,
No, unfortunately -- "the partition's OverSubscribe option takes precedence over the job's option"
Thanks for the suggestion, though!-dustin
On Mon, Mar 30, 2026 at 10:33 AM Guillaume COCHARD <guillaume.cochard@cc.in2p3.fr> wrote:
Hi,
Could --exclusive ( https://slurm.schedmd.com/sbatch.html#OPT_exclusive ) do the trick?
Guillaume
De: "Dustin Lang via slurm-users" <slurm-users@lists.schedmd.com>
À: "Slurm User Community List" <slurm-users@lists.schedmd.com>
Envoyé: Lundi 30 Mars 2026 16:12:11
Objet: [slurm-users] Shared queue: how to request full node with all resources?
Hi,
With a partition with "OverSubscribe=FORCE" set, is there a way to request all the node resources? I see "--mem=0" does that for memory. But I do not see an option to request all the CPUs and GRES/TRES such as GPUs. I tried "--nodes=1 --ntasks=1 --cpus-per-task=0", but "--cpus-per-task=0" does not do the same thing as "--mem=0".
In other words, is it possible to have a queue where nodes can be shared between jobs, but have a simple way for an sbatch script to request the full node with all its memory, cpus, and other resources? We have a heterogeneous cluster, so telling users (or jupyterhub scripts) to list exactly the resources they want doesn't really work.
thanks,dustin
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