We do the same thing. Our prolog has

============== # setup DCGMI job stats if [ -n "$CUDA_VISIBLE_DEVICES" ] ; then if [ -d /var/slurm/gpu_stats.run ] ; then if pgrep -f nv-hostengine >/dev/null 2>&1 ; then

groupstr=$(/usr/bin/dcgmi group -c J$SLURM_JOB_ID -a $CUDA_VISIBLE_DEVICES) groupid=$(echo $groupstr | awk '{print $10}')

/usr/bin/dcgmi stats -e /usr/bin/dcgmi stats -g $groupid -s $SLURM_JOB_ID

echo $groupid > /var/slurm/gpu_stats.run/J$SLURM_JOB_ID fi fi fi ======================

And our epilog has

====================== if [ -n "$CUDA_VISIBLE_DEVICES" ] ; then if [ -f /var/slurm/gpu_stats.run/J$SLURM_JOB_ID ] ; then if pgrep -f nv-hostengine >/dev/null 2>&1 ; then

groupid=$(cat /var/slurm/gpu_stats.run/J$SLURM_JOB_ID)

/usr/bin/dcgmi stats -v -j $SLURM_JOBID > /var/slurm/gpu_stats/$SLURM_JOBID if [ $? -eq 0 ] ; then /bin/rsync -a /var/slurm/gpu_stats/$SLURM_JOBID /cluster/batch/GPU/ /bin/rm -rf /tmp/gpuprocess.out # put the data in MYSQL database with perl script /cluster/batch/ADMIN/SCRIPTS/gpuprocess.pl $SLURM_JOB_ID > /tmp/gpuprocess.out 2>&1 if [ -s /tmp/gpuprocess.out ] ; then cat /tmp/gpuprocess.out | mail -s GPU_stat_process_error alert@nmr.mgh.harvard.edu fi fi

/usr/bin/dcgmi stats -x $SLURM_JOBID

/usr/bin/dcgmi group -d $groupid

/bin/rm /var/slurm/gpu_stats.run/J$SLURM_JOB_ID fi fi fi =======================

We also have a cron job on each node with GPUs that runs every 10 minutes to query dcgmi stats to write snapshot data on each GPU to the MYSQL database.

If you are on RHEL based boxes, the RPM you need from NVIDIA repos is datacenter-gpu-manager

On Thu, 17 Oct 2024 4:45am, Pierre-Antoine Schnell via slurm-users wrote:

   External Email - Use Caution 

Hello,

we recently started monitoring GPU usage on our GPUs with NVIDIA's DCGM: https: //secure-web.cisco.com/1KWAURVYDpmQYgABxXHpjl1HYdnLi1gOud_xdNWc3Pxea1JmFPHq-ARojCPZ7k2sn7nHLarge9d-vm4Yo0OwdO4jS-sxbbhr1mfGvdZ9653UOKmqqhQKiF7pNgB9ox8xEcuiLC-y_J7z3yC63xAdOL5pJKatcCaePuaoY4u2mTMIrOpNU-wulYVHWlLnv65d4AAFY6ipTgzp6As2PTZJlPcIP7RcToXJVUJhzDaMPYHRWsgRXaVU5156mcMRwn7bstXHH58PpmS2MkxpRJ0HGSA-Mjsmr6SKV3HixQxohY3OzyPnIslJt-kBC_AJvILCO/https%3A%2F%2Fdeveloper.nvidia.com%2Fblog%2Fjob-statistics-nvidia-data-center-gpu-manager-slurm%2F

We create a new dcgmi group for each job and start the statistics retrieval for it in a prolog script.

Then we stop the retrieval, save the dcgmi verbose stats output and delete the dcgmi group in an epilog script.

The output presents JobID, GPU IDs, runtime, energy consumed, and SM utilization, among other things.

We retrieve the relevant data into a database and hope to be able to advise our users on better practices based on the analysis of it.

Best wishes, Pierre-Antoine Schnell

Am 16.10.24 um 15:10 schrieb Sylvain MARET via slurm-users:

...

Hey guys !

I'm looking to improve GPU monitoring on our cluster. I want to install this https://secure-web.cisco.com/1fZ-E5mpOZvWDiBjPS6nGvTxPwlnYDhKBDJvrIMLGr18l4n... and saw in the README that it can support tracking of job id : https: //secure-web.cisco.com/1_JvkKV0Jm0yqxhTNbhLO9yC7U4G3sl2GSQRb2wrb-zRFRzd5kjwL7go8M2ESNdeIlaQM_peIOOHZCtWJibqHA4fl3Bk5xkr1tDe0QiOOCg8DLzw_OImhCSzXej8uZf3wHjpaQXCGtKzhUsW84CSsREcyBNTOTNjzAhr2HmDxYqMapS-TM8QFFrEB0u-3cJjdekUhw2rRhpZifMnj86S4nu6uG3Elyyla8GsaN8OC_Q6Jbu9kiW9hHGspRQ37Q3kbDIj7beBPkuik5eCPDtmabV-j2ppjd05G9eHZIrj9HAU2ZU3sIEsacOJ19eDUmNhl/https%3A%2F%2Fgithub.com%2FNVIDIA%2Fdcgm-exporter%3Ftab%3Dreadme-ov-file%23enabling-hpc-job-mapping-on-dcgm-exporter

However I haven't been able to see any examples on how to do it nor does slurm seem to expose this information by default. Does anyone do this here ? And if so do you have any examples I could try to follow ? If you have advise on best practices to monitor GPU I'd be happy to hear it out !

Regards, Sylvain Maret

-- Pierre-Antoine Schnell

Medizinische Universität Wien IT-Dienste & Strategisches Informationsmanagement Enterprise Technology & Infrastructure High Performance Computing

1090 Wien, Spitalgasse 23 Bauteil 88, Ebene 00, Büro 611

+43 1 40160-21304

pierre-antoine.schnell@meduniwien.ac.at

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