[Numpy-discussion] Introductory mail and GSoc Project "Vector math library integration"

Francesc Alted faltet at gmail.com
Wed Mar 11 13:54:34 EDT 2015

2015-03-08 21:47 GMT+01:00 Dp Docs <sdpan21 at gmail.com>:

> Hi all,
> I am a CS 3rd Undergrad. Student from an Indian Institute (III T). I
> believe I am good in Programming languages like C/C++, Python as I
> have already done Some Projects using these language as a part of my
> academics. I really like Coding (Competitive as well as development).
> I really want to get involved in Numpy Development Project and want to
> take  "Vector math library integration" as a part of my project. I
> want to here any idea from your side for this project.
> Thanks For your time for reading this email and responding back.

As Sturla and Gregor suggested, there are quite a few attempts to solve
this shortcoming in NumPy.  In particular Gregor integrated MKL/VML support
in numexpr quite a long time ago, and when combined with my own
implementation of pooled threads (behaving better than Intel's
implementation in VML), then the thing literally flies:


numba is also another interesting option and it shows much better compiling
times than the integrated compiler in numexpr.  You can see a quick
comparison about expected performances between numexpr and numba:


In general, numba wins for small arrays, but numexpr can achieve very good
performance for larger ones.  I think there are interesting things to
discover in both projects, as for example, how they manage memory in order
to avoid temporaries or how they deal with unaligned data efficiently.  I
would advise to look at existing docs and presentations explaining things
in more detail too.

All in all, I would really love to see such a vector math library support
integrated in NumPy because frankly, I don't have bandwidth for maintaining
numexpr anymore (and I am afraid that nobody else would jump in this ship

Good luck!


> My IRCnickname: dp
> Real Name: Durgesh Pandey.
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Francesc Alted
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