[Numpy-discussion] numpy blas running slow: how to check that it is properly linked

[David Cournapeau]

On Tue, Sep 6, 2011 at 5:12 PM, David Cottrell <david.cottrell at gmail.com> wrote:
> Actually this link: http://www.scipy.org/PerformanceTips seems to
> indicate that numpy.dot does use blas ...

This not true (you can check by looking into numpy/core/setup.py,
which explicitly checks for ATLAS for _dotblas). The idea is that
numpy can be built without a fortran compiler, but linking against
blas requires a fortran compiler. By depending on ATLAS, we can still
get a fast numpy.dot in the cases where a fortran compiler is not
available.

But strictly speaking, the code itself only depends on CBLAS
availability. The issue being that some CBLAS libraries still require
a fortran compiler to be linked against...

>
> Is there some way of running ldd on the install to see what libraries
> are being pulled in?

Yes, just use ldd on the .so inside a numpy installation. Generally,
python extensions are simply binaries that be be dlopened,

cheers,

David