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And note that for example on Apple M1 it's essentially impossible to beat an implementation that uses Apple's Accelerate library for things like matrix multipli
by orlp 4y ago
And note that for example on Apple M1 it's essentially impossible to beat an implementation that uses Apple's Accelerate library for things like matrix multiplication, because Apple uses undocumented instructions unavailable to the public in that library.
- orangepurple 4y agoDeprecated since version 1.20: The native libraries on macOS, provided by Accelerate, are not fit for use in NumPy since they have bugs that cause wrong output under easily reproducible conditions. If the vendor fixes those bugs, the library could be reinstated, but until then users compiling for themselves should use another linear algebra library or use the built-in (but slower) default, see the next section. Source: https://numpy.org/doc/stable/user/building.html https://numpy.org/doc/stable/user/building.html
- dagmx 4y agoAdded back the very next release https://numpy.org/doc/stable/release/1.21.0-notes.html https://numpy.org/doc/stable/release/1.21.0-notes.html > With the release of macOS 11.3, several different issues that numpy was encountering when using Accelerate Framework’s implementation of BLAS and LAPACK should be resolved.