On Thu, Oct 22, 2009 at 9:41 AM, Marshall Hampton <hampto...@gmail.com> wrote:
>
> You might find this helpful:
>
> http://www.scipy.org/PerformancePython
>
> Generally I think numpy's numerical linear algebra is comparable to
> matlab's.
>
> -Marshall
Here's a benchmark (the first thing I tried):
sage: a = random_matrix(RDF,2000)
sage: timeit('a*a')
5 loops, best of 3: 1.8 s per loop
sage: b = matlab('rand(2000)')
sage: timeit('b*b')
5 loops, best of 3: 3.4 s per loop
Sage is twice as fast. This is really benchmarking the numerical
linear algebra subsystem, which is ATLAS for Sage here.
The overhead of calling Matlab from Sage is insignificant compared to
the time of the benchmark (only a few characters get moved back and
forth).
The matlab above is:
Version 7.2.0.283 (R2006a)
January 27, 2006
so take this with a big grain of salt!
The above is on X4450's -- i.e., Dunnington Xeon's.
William
--
William Stein
Associate Professor of Mathematics
University of Washington
http://wstein.org
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