Hi,
long time ago I wrote a wrapper to to use optimised and parallelized math
functions from Intels vector math library
geggo/uvml: Provide vectorized math function (MKL) for numpy
<https://github.com/geggo/uvml>
I found it useful to inject (some of) the fast methods into numpy via
np.set_num_ops(), to gain more performance without changing my programs.
While this original project is outdated, I can imagine that a centralised way
to swap the implementation of math functions is useful. Therefor I suggest to
keep np.set_num_ops(), but admittedly I do not understand all the technical
implications of the proposed change.
best
Gregor
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