[SciPy-user] Numpy in parallel

Skipper Seabold jsseabold@gmail....
Thu Apr 23 15:56:35 CDT 2009


On Thu, Apr 23, 2009 at 4:26 AM, Ramon Crehuet <rcsqtc@iqac.csic.es> wrote:
> Dear all,
> I would like to use the 4 processors in my AMD Phenom machine to do some
> calcualtions with Numpy.
> According to:
> http://www.scipy.org/ParallelProgramming
> This can be achieved if numpy is compiled using a BLAS that is able to
> use multi-cores. I have installed the rpm numpy that comes with my
> Opensuse 11.0 distribution. Apparently only one processor is used when I
> calculate things like:
> c=numpy.dot(a,b)
> d=numpy.linalg.inv(c)
> My first question is: is this a good choice? Is this Numpy optimized for
> my arquitecture or I could do much better compiling ATLAS and Numpy from
> scratch? Or is Intel MKL better?

I don't know much about parallel processing or the actual dependence
on BLAS, but I have recently gone through trying to build Numpy and
Scipy with these dependencies from source on openSUSE and long story
short, I gave up and switched to a debian-based distribution (Kubuntu
Jaunty).  I never actually identified what the compiler issue was, but
Scipy didn't like how something was done in the build process.  I
can't recall the actual step that I think was hanging me up off the
top of my head.  You can see the discussion here:
<http://thread.gmane.org/gmane.comp.python.scientific.devel/10681/focus=10696>

Does your build of scipy pass all of the tests?  Also what does
show_config tell you?

-Skipper


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