[Numpy-discussion] low level optimization in NumPy and minivect
Wed Jun 26 06:30:17 CDT 2013
On 26 June 2013 09:05, Dag Sverre Seljebotn <firstname.lastname@example.org> wrote:
> On 06/25/2013 04:21 PM, Frédéric Bastien wrote:
>> I wasn't able to attend this year Scipy Conference. My tutorial proposal
>> was rejected and other deadline intefered with this conference date.
>> Will the presentation be recorded? If not, can you make the slide
>> What is your opinion on this question:
>> - Should other lib like NumPy/Theano/Cython/Numba base their elemwise
>> implemention (or part of it) on dynd or minivect? I know cython and
>> Numba do it, but it was before dynd and I don't know where dynd fit in
>> the big picture. Do dynd reuse minivect itself?
> Actually, I think the Cython branch with minivect support was in the end not
> merged, due to lack of interest/manpower to maintain support for
> vectorization in the long term (so it was better to not add the feature than
> have a badly supported feature).
> My understanding is that Numba is based on minivect and not on dynd, so it's
> more of a competitor.
> Perhaps Mark Florisson will be able to comment.
> Dag Sverre
Indeed, numba uses it for its array expression support, but it will
likely remove the minivect dependency and generate a simple loop nest
for now. I'm working on pykit now
(https://github.com/ContinuumIO/pykit) which similarly to minivect
defines its own intermediate representation, with array expressions in
the form of map/reduce/scan/etc functions. The project has a broader
scope than minivect, to be used by projects like numba, what but a
"minivect baked in".
As such, minivect isn't really maintained any longer, and I wouldn't
recommend anyone using the code at this point (just maybe some of the
More information about the NumPy-Discussion