Hi everyone,
sorry if this has already been answered somewhere, but my quick search didn’t really give me an answer.
I was wondering if there is any possible performance regression when setting JULIA_NUM_THREADS larger than the actual available threads. On my laptop there’s no issue, as Julia automatically sets it too the maximum threads available, even if I set the environment variable too large. For the cluster I’m using I allocate some of the threads and set the number accordingly. The issue is that the number of allocated threads is not the same for Intel and AMD cores, i.e. when allocating 16 “CPUs” through the LSF manager I get 16 threads on AMD and 32 on Intel. Should I just always set JULIA_NUM_THREADS to 32 and it doesn’t matter for the AMD cores, or are there any caveats? I don’t know prior to the run on which node the job will run.
Yes I do. The question is the following: Should I set my JULIA_NUM_THREADS to the number of possible hyperthreads with an Intel processor, or should I try to get the right number for the AMD processors? Would there be a noticable difference between 2x too many threads? Maybe this makes more sense if I highlight also that these number of threads are not all the threads available on one node, just the ones I am able to use.