Hi Stefan & All,

On Sun, May 25, 2008 at 8:59 PM, Stéfan van der Walt wrote:
> Hi Andrea
>
> 2008/5/25 Andrea Gavana <[EMAIL PROTECTED]>:
>>> When you bench the Cython code, you'll have to take out the Python
>>> calls (for checking dtype etc.), otherwise you're comparing apples and
>>> oranges.  After I tweaked it, it ran roughly the same time as
>>> Francesc's version.  But like I mentioned before, the Fortran results
>>> should trump all, so what is going on here?
>>
>> I thought I had removed the Python checks from the Cython code (if you
>> look at the attached files), but maybe I haven't removed them all...
>> about Fortran, I have no idea: I have 6 different implementations in
>> Fortran, and they are all slower than the pure NumPy ones. I don't
>> know if I can optimiza them further (I have asked to a Fortran
>> newsgroup too, but no faster solution has arisen). I am not even sure
>> if the defaults f2py compiler options are already on "maximum
>> optimization" for Fortran. Does anyone know if this is true? Maybe
>> Pearu can shed some light on this issue...
>
> Here are the timings on my machine.  You were right -- you did remove
> the type checks in the Cython code.  It turns out the bottleneck was
> the "for i in range" loop.  I was under the impression that loop was
> correctly optimised; I'll have a chat with the Cython developers.  If
> I change it to "for i in xrange" or "for i from 0 <= i < n" the speed
> improves a lot.
>
> I used gfortran 4.2.1, and as you can see below, the Fortran
> implementation beat all the others.
>
> ---------------------------------------------------------------------
>                       Number Of Cells: 300000
> ---------------------------------------------------------------------
> | Rank |      Method Name      | Execution Time | Relative Slowness |
> ---------------------------------------------------------------------
>   1       Fortran 5 (James)       0.01854820          1.00000
>   2       Fortran 6 (James)       0.01882849          1.01511
>   3        Fortran 1 (Mine)       0.01917751          1.03393
>   4      Fortran 4 {Michael)      0.01927021          1.03893
>   5        Fortran 2 (Mine)       0.01937311          1.04447
>   6    NumPy 4 (Nathan-Vector)    0.02008982          1.08311
>   7        NumPy 2 (Nathan)       0.02046990          1.10361
>   8        NumPy 5 (Andrea)       0.02108521          1.13678
>   9       NumPy 1 (Francesc)      0.02211959          1.19255
>  10        Cython (Stefan)        0.02235680          1.20533
>  11        Fortran 3 (Alex)       0.02486629          1.34063
>  12        NumPy 3 (Peter)        0.05020461          2.70671
> ---------------------------------------------------------------------

Thank you for the tests you have run. I have run mine with Compaq
Visual Fortran 6.6 on Windows XP, and I assume I can not use gfortran
with MS visual studio 2003 (which is the compiler Python is built
with). So the only option I have is to try Intel Visual Fortran, which
I will do tomorrow, or stick with the numpy implementation as it looks
like there is nothing more I can do (even with sorted arrays or using
another approach, and I can't think of anything else) to speed up my
problem.

A big thank you to everyone in this list, you have been very kind and helpful.

Andrea.

"Imagination Is The Only Weapon In The War Against Reality."
http://xoomer.alice.it/infinity77/
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