[SciPy-User] In which numpy modules should MKL be better then ATLAS

[Klonuo Umom]

It's old Intel P4 3Ghz
ATLAS/LAPACK are build from source so maybe more optimized


On Sat, Oct 1, 2011 at 12:23 PM, Dag Sverre Seljebotn <
d.s.seljebotn at astro.uio.no> wrote:

> On 10/01/2011 11:55 AM, Klonuo Umom wrote:
> > I had a chance to test this sample on different setups on same PC:
> >
> > import numpy as np
> > A=np.ones((1000,1000))
> > B=np.ones((1000,1000))
> > %timeit np.dot(A, B)
> >
> > because of OS reinstalling.
> >
> > 1x = ATLAS on Linux (reference speed)
> > 2x = MKL with GNU compilers on Linux
> > 2x = MKL with Intel compilers on Windows 7
> > 30x = bare numpy
> >
> > I didn't plan to do this so I didn't test additional calculations, and I
> > was using latest version to date for all products.
> >
> > On Internet I usually find that MKL should outperform ATLAS. I'm curious
> > what would linalg module testing give, but as said I didn't test it. So
> > in which modules should user expect impact of MKL over ATLAS? In matrix
> > dot product obviously not.
>
> What CPU are you on? MKL is tuned for Intel CPUs, perhaps ATLAS
> outperforms it on AMD ones.
>
> Dag Sverre
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