ENH: speed up ufunc reduce argument parsing #4174
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PyArg_ParseTupleAndKeywords makes out about 20% of the runtime of small
reductions. Replace it with faster parsing using pre-interned python
strings. This improves performance by about 15% for reductions in the
order of 100 elements.
Error handling is done by calling PyArg_ParseTupleAndKeywords after the
fast parsing fails.
before:
d = np.arange(100)
%timeit np.sum(d)
100000 loops, best of 3: 4.79 µs per loop
after:
d = np.arange(100)
%timeit np.sum(d)
100000 loops, best of 3: 4.03 µs per loop
Contributor
Author
|
this is still a prototype PR looking for comments on implementation. |
Contributor
Author
|
hm it might be possible to avoid adding a faster parser by changing some wrappers to not use keyword arguments, investigating. |
Contributor
Author
|
sort of obsoleted by dropping the use of keyword arguments for the top level functions. I'll keep the branch around as the approach itself might be worthwhile for functions which use many keyword arguments. The array constructor could be a candidate. |
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PyArg_ParseTupleAndKeywords makes out about 20% of the runtime of small
reductions. Replace it with faster parsing using pre-interned python
strings. This improves performance by about 15% for reductions in the
order of 100 elements.
Error handling is done by calling PyArg_ParseTupleAndKeywords after the
fast parsing fails.
before:
after: