How to get the same MPI/OpenMP mapping using dask-jobqueue

Hi everybody,

I am using the following script to run a hybrid (MPI/OpenMP) application in a Cluster (each node in the cluster has 20 physical cores) via SLURM

#!/bin/bash
JOB=458754
for nrun in {1..10}
do
for npop in 600
do
  for niter in 100
  do
     for boundary in reflecting
     do
SAIDA=$(sbatch -o "${nrun}runs${npop}x${niter}_${boundary}_gbest_canonical_cc_em_375x369_5000_2_2.txt" --ntasks=300 --cpus-per-task=2 --ntasks-per-node=10 --ntasks-per-socket=5 -p cluster128g --requeue ./script.sh $nrun $npop $niter $boundary 2)
    JOB=$SAIDA
    done
  done
done
done
echo "last job was $JOB

Thus, I map 10 MPI process on each node of the cluster, each of which spawns two OpenMP threads (10 MPI x 2 OpenMP threads= 20cores). I rewrote my application in python and I would like to use dask to parallelize it. However, I couldn’t map more than one worker in a node in my first attempts. How can I do that? I mean map more than one dask worker in the nodes such way I take advantage of all resources. I looked for some example trought the issues list but I could not find any. Some idea?

Thanks

[ofmla]

@guillaumeeb thanks for your readiness to support and assist and sorry for the late reply, I had a deadline lately which took my time. I am still confused about on dask-jobqueue operation and I am facing some issues. Anyway, I will perform some tests following your comment and let you know if it works.

[guillaumeeb]

Closing this issue as stale. @ofmla if you ever work on this again, feel free to reopen.