On Thu, Mar 8, 2018 at 4:52 AM, Gregor Thalhammer <gregor.thalham...@gmail.com> wrote: > > 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 > > 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 While this original project is outdated, I can imagine that a centralised 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.
There may still be a case for being able to swap out the functions that do the actual work, i.e., the parts of the ufuncs that are called once any conversion to ndarray has been done. -- Marten _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
