[Numpy-discussion] Execution time difference between 2.7 and 3.2 using numpy

Chris Barker - NOAA Federal chris.barker@noaa....
Fri Mar 22 23:05:11 CDT 2013


On Fri, Mar 22, 2013 at 2:39 PM, Colin J. Williams
<cjwilliams43@gmail.com> wrote:
> I have updated to numpy 1.7.0 for each of the Pythons 2.7.3, 3.2.3 and
> 3.3.0.
...
> The tests, which are available
> here(http://web.ncf.ca/cjw/FP%20Summary%20over%20273-323-330.txt), show that
> 3.2 is slower, but not to the same degree reported before.

Have posted your test code anywhere? Anyway, depending on how you did
your timings, that looks to me like 3.* is a bit faster with small
data, and pretty much within measurement error for the large datasets.

And if the large ones are doing things with really big arrays (I'm
assuming pretty big, as you're getting close to 32 bit memory
limits...), then it's really hard to imagine how python version could
make a noticeable difference -- the real work would be in the numpy
code, and that's exactly the same on all python versions.

If you are using BLAS or LAPACK stuff, then there might be some
differences with the different builds, though I wouldn't expect so if
you ar getting them from the same source.

-Chris


-- 

Christopher Barker, Ph.D.
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