Hi, I would like to ask you the help check :
I am trying to use openmp queues in the cluster to run gcal.py and I put the command about the number of threads to use in the head of the script like this :
"
!/usr/bin/env python
import os
os.environ['OMP_NUM_THREADS']='10'
"
But I am not sure this is correct, since when I set OMP_NUM_THREADS=10, the number of cores
the job use is actually about 6. When I set OMP_NUM_THREADS=4, the actually number of cores
the job use is about 3.
And to use openmp, it only requires that the jobs are submitted to the queues for openmp, right ?
Of course, I can set the number of threads as environmental variable like stated above.
In addition, could gcal.py be parallel processed by mvapich2 ? I tested a job in mvapich2 queue and
it seems that mvapich2 process the same job faster than openmp does, but I am not sure the job
run properly.
Hi, I would like to ask you the help check : I am trying to use openmp queues in the cluster to run gcal.py and I put the command about the number of threads to use in the head of the script like this : "
!/usr/bin/env python
import os
os.environ['OMP_NUM_THREADS']='10'
" But I am not sure this is correct, since when I set OMP_NUM_THREADS=10, the number of cores the job use is actually about 6. When I set OMP_NUM_THREADS=4, the actually number of cores the job use is about 3.
And to use openmp, it only requires that the jobs are submitted to the queues for openmp, right ? Of course, I can set the number of threads as environmental variable like stated above.
In addition, could gcal.py be parallel processed by mvapich2 ? I tested a job in mvapich2 queue and it seems that mvapich2 process the same job faster than openmp does, but I am not sure the job run properly.
Thanks for your attention.