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submitted 2 months ago by [email protected] to c/[email protected]
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[-] [email protected] 41 points 2 months ago

Of the ways you listed the only one that will actually take advantage of a multi core CPU is multiprocessing

[-] [email protected] 11 points 2 months ago

yup, that's true. most meaningful tasks are io-bound so "parallel" basically qualifies as "whatever allows multiple threads of execution to keep going". if you're doing numbercrunching in pythen without a proper library like pandas, that can parallelize your calculations, you're doing it wrong.

[-] [email protected] 8 points 2 months ago* (last edited 2 months ago)

I’ve used multiprocessing to squeeze more performance out of numpy and scipy. But yeah, resorting to multiprocessing is a sign that you should be dropping into something like Rust or a C variant.

[-] [email protected] 1 points 2 months ago

Most numpy array functions already utilize multiple cores, because they're optimized and written in C

this post was submitted on 26 Mar 2025
547 points (97.1% liked)

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