If you run "scontrol show jobid <jobid>" of your pending job with the "(Resources)" tag you may see more about what is unavailable to your job. Slurm default configs can cause an entire compute node of resources to be "allocated" to a running job regardless of whether it needs all of them or not so you may need to alter one or both of the following settings to allow more than one job to run on a single node at once. You'll find these in your slurm.conf. Don't forget to "scontrol reconf" and even potentially restart both "slurmctld" & "slurmd" on your nodes if you do end up making changes.

SelectType=select/cons_tres SelectTypeParameters=CR_Core_Memory

I hope this helps.

Kind regards, Jason

----

Jason Macklin

Manager Cyberinfrastructure, Research Cyberinfrastructure

860.837.2142 t | 860.202.7779 m

jason.macklin@jax.org

The Jackson Laboratory

Maine | Connecticut | California | Shanghai

www.jax.orghttp://www.jax.org

The Jackson Laboratory: Leading the search for tomorrow's cures

________________________________ From: slurm-users slurm-users-bounces@lists.schedmd.com on behalf of slurm-users-request@lists.schedmd.com slurm-users-request@lists.schedmd.com Sent: Friday, January 19, 2024 9:24 AM To: slurm-users@lists.schedmd.com slurm-users@lists.schedmd.com Subject: [EXTERNAL]slurm-users Digest, Vol 75, Issue 31

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Today's Topics:

1. Re: Need help with running multiple instances/executions of a batch script in parallel (with NVIDIA HGX A100 GPU as a Gres) (Marko Markoc) 2. Re: Need help with running multiple instances/executions of a batch script in parallel (with NVIDIA HGX A100 GPU as a Gres) (?mit Seren)

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Message: 1 Date: Fri, 19 Jan 2024 06:12:24 -0800 From: Marko Markoc mmarkoc@pdx.edu To: Slurm User Community List slurm-users@lists.schedmd.com Subject: Re: [slurm-users] Need help with running multiple instances/executions of a batch script in parallel (with NVIDIA HGX A100 GPU as a Gres) Message-ID: CABnuMe4JTA0e6=VbO8D+To=8FGO+3Byv1dK_MC+OuRitzN5dXg@mail.gmail.com Content-Type: text/plain; charset="utf-8"

+1 on checking the memory allocation. Or add/check if you have any DefMemPerX set in your slurm.conf

On Fri, Jan 19, 2024 at 12:33?AM mohammed shambakey shambakey1@gmail.com wrote:

Hi

I'm not an expert, but is it possible that the currently running jobs is consuming the whole node because it is allocated the whole memory of the node (so the other 2 jobs had to wait until it finishes)? Maybe if you try to restrict the required memory for each job?

Regards

On Thu, Jan 18, 2024 at 4:46?PM ?mit Seren uemit.seren@gmail.com wrote:

...

This line also has tobe changed:

#SBATCH --gpus-per-node=4 ? #SBATCH --gpus-per-node=1

--gpus-per-node seems to be the new parameter that is replacing the --gres= one, so you can remove the ?gres line completely.

Best

?mit

*From: *slurm-users slurm-users-bounces@lists.schedmd.com on behalf of Kherfani, Hafedh (Professional Services, TC) hafedh.kherfani@hpe.com *Date: *Thursday, 18. January 2024 at 15:40 *To: *Slurm User Community List slurm-users@lists.schedmd.com *Subject: *Re: [slurm-users] Need help with running multiple instances/executions of a batch script in parallel (with NVIDIA HGX A100 GPU as a Gres)

Hi Noam and Matthias,

Thanks both for your answers.

I changed the ?#SBATCH --gres=gpu:4? directive (in the batch script) with ?#SBATCH --gres=gpu:1? as you suggested, but it didn?t make a difference, as running this batch script 3 times will result in the first job to be in a running state, while the second and third jobs will still be in a pending state ?

[slurmtest@c-a100-master test-batch-scripts]$ cat gpu-job.sh

#!/bin/bash

#SBATCH --job-name=gpu-job

#SBATCH --partition=gpu

#SBATCH --nodes=1

#SBATCH --gpus-per-node=4

#SBATCH --gres=gpu:1 # <<<< Changed from ?4? to ?1?

#SBATCH --tasks-per-node=1

#SBATCH --output=gpu_job_output.%j

#SBATCH --error=gpu_job_error.%j

hostname

date

sleep 40

pwd

[slurmtest@c-a100-master test-batch-scripts]$ sbatch gpu-job.sh

Submitted batch job *217*

[slurmtest@c-a100-master test-batch-scripts]$ squeue

         JOBID PARTITION     NAME     USER ST       TIME  NODES

NODELIST(REASON)

           217       gpu  gpu-job slurmtes  R       0:02      1

c-a100-cn01

[slurmtest@c-a100-master test-batch-scripts]$ sbatch gpu-job.sh

Submitted batch job *218*

[slurmtest@c-a100-master test-batch-scripts]$ sbatch gpu-job.sh

Submitted batch job *219*

[slurmtest@c-a100-master test-batch-scripts]$ squeue

         JOBID PARTITION     NAME     USER ST       TIME  NODES

NODELIST(REASON)

           219       gpu  gpu-job slurmtes *PD*       0:00      1

(Priority)

           218       gpu  gpu-job slurmtes *PD*       0:00      1

(Resources)

           217       gpu  gpu-job slurmtes  *R*       0:07      1

c-a100-cn01

Basically I?m seeking for some help/hints on how to tell Slurm, from the batch script for example: ?I want only 1 or 2 GPUs to be used/consumed by the job?, and then I run the batch script/job a couple of times with sbatch command, and confirm that we can indeed have multiple jobs using a GPU and running in parallel, at the same time.

Makes sense ?

Best regards,

*Hafedh *

*From:* slurm-users slurm-users-bounces@lists.schedmd.com *On Behalf Of *Bernstein, Noam CIV USN NRL (6393) Washington DC (USA) *Sent:* jeudi 18 janvier 2024 2:30 PM *To:* Slurm User Community List slurm-users@lists.schedmd.com *Subject:* Re: [slurm-users] Need help with running multiple instances/executions of a batch script in parallel (with NVIDIA HGX A100 GPU as a Gres)

On Jan 18, 2024, at 7:31 AM, Matthias Loose m.loose@mindcode.de wrote:

Hi Hafedh,

Im no expert in the GPU side of SLURM, but looking at you current configuration to me its working as intended at the moment. You have defined 4 GPUs and start multiple jobs each consuming 4 GPUs each. So the jobs wait for the ressource the be free again.

I think what you need to look into is the MPS plugin, which seems to do what you are trying to achieve: https://slurm.schedmd.com/gres.html#MPS_Management

I agree with the first paragraph. How many GPUs are you expecting each job to use? I'd have assumed, based on the original text, that each job is supposed to use 1 GPU, and the 4 jobs were supposed to be running side-by-side on the one node you have (with 4 GPUs). If so, you need to tell each job to request only 1 GPU, and currently each one is requesting 4.

If your jobs are actually supposed to be using 4 GPUs each, I still don't see any advantage to MPS (at least in what is my usual GPU usage pattern): all the jobs will take longer to finish, because they are sharing the fixed resource. If they take turns, at least the first ones finish as fast as they can, and the last one will finish no later than it would have if they were all time-sharing the GPUs. I guess NVIDIA had something in mind when they developed MPS, so I guess our pattern may not be typical (or at least not universal), and in that case the MPS plugin may well be what you need.

-- Mohammed