[Numpy-discussion] performance matrix multiplication vs. matlab

[David Cournapeau]

David Warde-Farley wrote:
> On 4-Jun-09, at 5:03 PM, Anne Archibald wrote:
>
>   
>> Apart from the implementation issues people have chimed in about
>> already, it's worth noting that the speed of matrix multiplication
>> depends on the memory layout of the matrices. So generating B instead
>> directly as a 100 by 500 matrix might affect the speed substantially
>> (I'm not sure in which direction). If MATLAB's matrices have a
>> different memory order, that might be a factor as well.
>>     
>
> AFAIK Matlab matrices are always Fortran ordered.
>
> Does anyone know if the defaults on Mac OS X (vecLib/Accelerate)  
> support multicore? Is there any sense in compiling ATLAS on OS X (I  
> know it can be done)?
>   

It may be worthwhile if you use a recent gcc and recent ATLAS.
Multithread support is supposed to be much better in 3.9.* compared to
3.6.* (which is likely the version used on vecLib/Accelerate). The main
issue I could foresee is clashes between vecLib/Accelerate and Atlas if
you mix softwares which use one or the other together.

For the OP question: recent matlab versions use the MKL, which is likely
to give higher performances than ATLAS, specially on windows (compilers
on that platform are ancient, as building atlas with native compilers on
windows requires super-human patience).

David