Problem allocating 24 workers using parpool
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I am trying to execute a few jobs in parallel on a computing cluster. The maximum number of workers available per node is 24. When I execute the job, some jobs are allocated 24 workers, some are allocated 12, whereas some jobs are only running on one worker. What could possibly be the reason for this when the job script is the same for all jobs requesting for 24 workers per node? I looked at the job output for the job running on one worker and it says "
>> >> >> Starting parallel pool (parpool) using the 'local' profile ...
>> >> >> >> >> Starting parallel pool (parpool) using the 'local' profile ..."
This shows that the parpool did start for this job, however, only one worker was allocated. When I check the output of a job running on 24 workers, it says
">> >> >> Starting parallel pool (parpool) using the 'local' profile ...
Connected to the parallel pool (number of workers: 24)."
I am trying to run all jobs using all 24 workers for each job but I am not able to. Any help would be greatly appreciated.
3 Comments
Raymond Norris
on 18 Sep 2020
Hi Geeta,
It sounds like you're running MATLAB jobs on an HPC cluster via a jobscript. Your submitting N jobscripts, with each jobscript requesting 24 procs per node. The MATLAB code is calling parpool, parfor, or spmd, etc.
- Are each of the MATLAB jobs running the same exact code?
- How are parallel pools starting up? Is parpool being called explicitly and if so with what size?
- If parpool is not passed an argument, the default size is min(12,24) ==> 12 workers
- If parpool is not called, parfor/spmd will start a pool (by default), which follows the same patter of min(12,24) ==> 12 workers.
- The min(12,24) is because 12 is the default pool size and 24 is the number of cores found on the node (or within cgroup).
Can you share a sample jobscript and MATLAB code?
Raymond
Geeta Garg
on 18 Sep 2020
Edited: Geeta Garg
on 18 Sep 2020
Geeta Garg
on 22 Sep 2020
Edited: Geeta Garg
on 22 Sep 2020
Answers (1)
Mohammad Sami
on 18 Sep 2020
Edited: Mohammad Sami
on 18 Sep 2020
Perhaps you can try
core = feature('numcores');
pool = parpool('local',core);
disp(['Pool has been started with Num Workers ' num2str(pool.NumWorkers)]);
Additionally you can try restarting the pool, if the workers are less then the number of cores.
retries = 0;
retry_limit = 3;
while (pool.NumWorkers < core)
retries = retries + 1;
disp('Restarting parallel pool');
delete(pool);
pool = parpool('local',core);
disp(['Pool has been started with Num Workers ' num2str(pool.NumWorkers)]);
if(retries >= retry_limit)
break;
end
end
1 Comment
Geeta Garg
on 18 Sep 2020
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