[Numpy-discussion] NumPy benchmark

lorenzo bolla lbolla@gmail....
Wed Apr 18 02:42:24 CDT 2007


the amazing performance of C++ code does not surprise me: a tenfold
improvement of the simple Python/Numpy code can be achieved with
weave.inline or Pyrex.

Hence your benchmarks seems to confirm that "weaved" or "pyrexed" code run
as fast as C++ compiled one.

Moreover, from your numbers, I can tell that compiling numpy with gcc or icc
makes no big difference.

Am I correct?

If yes, let me know if I can add this info to the scipy wiki: I'm preparing
an extention to this page http://www.scipy.org/PerformancePython.

cheers,
lorenzo




On 4/17/07, rex <rex@nosyntax.com> wrote:
>
> lorenzo bolla <lbolla@gmail.com> [2007-04-17 00:37]:
> > as soon as you do it, I'd like to compare them with the benchmarks I
> posted
> > here few days ago (compiled with gcc):
>
>
> http://lbolla.wordpress.com/2007/04/11/numerical-computing-matlab-vs-pythonnumpyweave/
>
> Thanks for the link.
>
> I haven't built numpy with MKL 9.1 yet, but here are some results
> running laplace.py using MKL 8.1. The CPU is a Core 2 Duo (currently)
> overclocked to 2.94 GHz (it will run at 3.52 GHz).
>
> Using Python2.5 compiled with icc 9.1, numpy built with MKL 8.1
> Doing 100 iterations on a 500x500 grid
> numeric took 1.53 seconds
> slow (100 iterations) took 130.02 seconds
> slow with Psyco (100 iterations) took 107.91 seconds
>
> Python compiled with icc takes 85 times longer to run this benchmark
> than Python/NumPy does.
>
> Using Python2.5 compiled with gcc, numpy built with MKL 8.1
> Doing 100 iterations on a 500x500 grid
> numeric took 1.57 seconds
> slow (100 iterations) took 154.29 seconds
> slow with Psyco (100 iterations) took 119.88 seconds
>
> Python compiled with gcc takes 101 times longer to run this benchmark
> than Python/NumPy/icc does.
>
> The C++ version compiled with gcc 4.1.2 runs in .19 seconds.
>
> -rex
> --
> I liked Occam's razor so much I bought the company.
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