Would MaxCPUsPerNode set at the partition level help?

Here's the snippet from the man page:

MaxCPUsPerNode
Maximum number of CPUs on any node available to all jobs from this partition. 
This can be especially useful to schedule GPUs. For example a node can be 
associated with two Slurm partitions (e.g. "cpu" and "gpu") and the 
partition/queue "cpu" could be limited to only a subset of the node's CPUs, 
insuring that one or more CPUs would be available to jobs in the "gpu" 
partition/queue.

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> On Apr 6, 2015, at 11:25 PM, Novosielski, Ryan <[email protected]> 
> wrote:
> 
> 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. 
> 
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>> On Apr 6, 2015, at 20:17, Ryan Cox <[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
>>> 
>>> 

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