Originally posted by coder
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Intel Contributes AVX-512 Optimizations To Numpy, Yields Massive Speedups
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Originally posted by RedEyed View Post
Those how buy hw for compute, buy Intel + NVIDIA, rather than AMD + NVIDIA
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Originally posted by numacross View Post
EPYC is more performant (apart from AVX-512), has more PCIe lanes, was first to market with PCIe 4.0 and is cheaper than Xeon. All the deployments I know of went for AMD, and only a few ended up with Intel because of supply issues.
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Originally posted by jabl View Post
It's about using SVML, which provides very fast and vectorized (including avx-512 it appears) versions of math functions like sin(), cos(), log(), gamma() etc. etc.
Unfortunately SVML isn't open source, so you're not gonna see this performance with the out of the box numpy on your Linux distro.
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Originally posted by smitty3268 View Post
It looks like the code this is using is BSD licensed, available here: https://github.com/numpy/svml
Anyway, I believe ctlansdown is right and numpy must not have been using vectorized instructions at all on certain operations in order to get this kind of speedup.
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Originally posted by coder View PostIf Zen 4 has AVX-512 as rumored, AMD should send Intel a "thank you" cake. Considering Alder Lake removed AVX-512, this is a double-win for AMD.
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Originally posted by cl333r View Post
I think @clownstown meant that sin, cos don't seem complicated to need extra CPU acceleration, right?
And no, since x87 FPU's haven't had hardware implementations of math functions (and in many respects, even the x87 HW implementations were/are shit), library implementations have to implement it using various numerical algorithms based on +, -, *, /.
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Originally posted by coder View PostIf Zen 4 has AVX-512 as rumored, AMD should send Intel a "thank you" cake. Considering Alder Lake removed AVX-512, this is a double-win for AMD.
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