[Numpy-discussion] Dropping support for Accelerate/veclib?

Ralf Gommers ralf.gommers@gmail....
Tue Jun 11 15:45:05 CDT 2013


On Tue, Jun 11, 2013 at 2:09 PM, Matthew Brett <matthew.brett@gmail.com>wrote:

> Hi,
>
> On Tue, Jun 11, 2013 at 5:17 AM, Pauli Virtanen <pav@iki.fi> wrote:
> > David Cournapeau <cournape <at> gmail.com> writes:
> > [clip]
> >> What is the default ABI used on homebrew ? I think we should just
> >> follow that, given that Apple cannot figure it out.
> >
> > I think for Scipy homebrew uses the Gfortran ABI:
> > https://trac.macports.org/browser/trunk/dports/python/py-scipy/Portfile
> >
> > But that's probably the wrong thing to do, it doesn't work:
> > http://trac.macports.org/ticket/36694
> >
> > For Octave, they have -ff2c:
> > https://trac.macports.org/browser/trunk/dports/math/octave/Portfile
> >
> >     ***
> >
> > A third option (maybe the best one) could be to add an ABI check
> > to numpy.distutils BLAS/LAPACK detection --- compile a small test
> > program that checks SDOT/CDOTU/DDOT etc., and refuse to use the
> > BLAS/LAPACK libraries if they give incorrect results. After that,
> > we can also remove the sdot/cdotu wrappers.
> >
> > This approach is used by Octave.
> >
> > This leaves the problem of dealing with Fortran ABI to those in
> > charge of the build environment, e.g., macports, Enthought, ...,
> > who are also in the best position to pick the correct solution
> > per each platform supported.
> >
> > AFAIK custom compiler flags can be injected via FOPT/FFLAGS/LDFLAGS,
> > so doing something like
> >
> >     export FOPT="-ff2c"
> >
> > or
> >
> >     export LDFLAGS="-ldotwrp -lblas"
> >
> > works? This makes things a bit more complicated to the builder, an
> > issue that can be solved with documentation, and keeping that up to
> > date is easier than hardcoding stuff into numpy.distutils.
>
> What will be the performance drop for the default OSX installer
> version of numpy, if we drop Accelerate / veclib support?
>

Answer on scipy-dev:
http://article.gmane.org/gmane.comp.python.scientific.devel/17864
Summary: it depends.
If anyone knows of better benchmarks, please share.

Joern Hees just wrote up how to install with OpenBLAS, if you want to know
for your application you can give it a try:
http://joernhees.de/blog/2013/06/08/mac-os-x-10-8-scientific-python-with-homebrew/

Ralf
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