On Wed, Aug 18, 2021 at 10:37 PM Joao S. O. Bueno <jsbu...@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 _______________________________________________ Python-ideas mailing list -- python-ideas@python.org To unsubscribe send an email to python-ideas-le...@python.org https://mail.python.org/mailman3/lists/python-ideas.python.org/ Message archived at https://mail.python.org/archives/list/python-ideas@python.org/message/AAIOSDVRE57G3ARY6YGNATW4YBP5G7UA/ Code of Conduct: http://python.org/psf/codeofconduct/
