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UID:pretalx-2023-DF8PVV@cfp.scipy.org
DTSTART;TZID=CST:20230712T104500
DTEND;TZID=CST:20230712T111500
DESCRIPTION:While the NumPy C API lets developers write C that builds or ev
 aluates arrays\, just writing C is often not enough to outperform NumPy. N
 umPy's usage of Single Instruction Multiple Data routines\, as well as mul
 ti-source compiling\, provide optimizations that are impossible to beat wi
 th simple C. This presentation offers principles to help determine if an a
 rray-processing routine\, implemented as a C-extension\, might outperform 
 NumPy called from Python. A C-extension implementing a narrow use case of 
 the ``np.nonzero()`` routine will be studied as an example.
DTSTAMP:20260315T233124Z
LOCATION:Amphitheater 204
SUMMARY:Out-Performing NumPy is Hard: When and How to Try with Your Own C-E
 xtensions - Christopher Ariza
URL:https://cfp.scipy.org/2023/talk/DF8PVV/
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