On Wed, Aug 18, 2021 at 10:37 PM Joao S. O. Bueno <jsbueno@python.org.br> wrote:
So, It is out of scope of Pythonmultiprocessing, and, as I perceive it, from the stdlib as a whole to be able to allocate specific cores for each subprocess - that is automatically done by the O.S. (and of course, the O.S. having an interface for it, one can write a specific Python library which would allow this granularity, and it could even check core capabilities).
Python does have a way to set processor affinity, so it's entirely possible that this would be possible. Might need external tools though.
As it stands however, is that you simply have to change your approach: instead of dividing yoru workload into different cores before starting, the common approach there is to set up worker processes, one per core, or per processor thread, and use those as a pool of resources to which you submit your processing work in chunks. In that way, if a worker happens to be in a faster core, it will be done with its chunk earlier and accept more work before slower cores are available.
But I agree with this. Easiest to just subdivide further. ChrisA