[Numpy-discussion] New NEP: merging multiarray and umath

[Charles R Harris]

On Thu, Mar 8, 2018 at 9:20 AM, Charles R Harris <charlesr.harris at gmail.com>
wrote:

>
>
> On Thu, Mar 8, 2018 at 2:52 AM, Gregor Thalhammer <
> gregor.thalhammer at 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
>> <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.
>>
>
> I think that was much of the original motivation for `set_num_ops` back in
> the Numeric days, where there was little commonality among platforms and
> getting hold of optimized libraries was very much an individual thing. The
> former cblas module, now merged with multiarray, was present for the same
> reasons.
>
>
>>
>> While this original project is outdated, I can imagine that a centralised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.
>>
>
> I suppose we could set it up to detect and use an external library during
> compilation. The CBLAS implementations currently do that and should pick up
> the MKL version when available. Where are the MKL functions you used
> presented? That is an admittedly lower level interface, however.
>
>
Note that Intel is also working to support NumPy and intends to use the
Intel optimizations as part of that.


Chuck
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