Control threads number
Opened this issue · 2 comments
Is there a way to control a thread number used by the program? When submitting jobs to LSF cluster, every queue has the maximum number of threads allowed for the job, so if the program uses more then allowed, it gets killed
Is it possible to request a limited number of CPUs at the job submission step for LSF? For example, when I run PBS jobs, I can request resource based on my need as follows:
#PBS -l nodes=1:ppn=4,mem=20gb
I don't have too much experience in multi-thread programming :( and not quite sure about how to control the thread number..
The threads number is not the same as CPUs or processes number. It's more like another level of parallelization that, I guess, we cannot control in TensorFlow. In my case, I had a limitation of 200 threads, but Leopard needed 593
Wed Dec 11 23:02:28: Resource usage collected.
MEM: 33 Gbytes; SWAP: 83 Gbytes; NTHREAD: 593
PGID: 21493; PIDs: 21493 21505 21509 21591 21623 21624
21625 21626 21627 21628
Btw, what is the best configuration to run Leopard. I mean, CPU, RAM, nodes number?