[Numpy-discussion] 64-bit windows numpy / scipy wheels for testing

[David Cournapeau]

On Fri, May 9, 2014 at 11:49 AM, Julian Taylor <
jtaylor.debian at googlemail.com> wrote:

> On 09.05.2014 12:42, David Cournapeau wrote:
> >
> >
> >
> > On Fri, May 9, 2014 at 1:51 AM, Matthew Brett <matthew.brett at gmail.com
> > <mailto:matthew.brett at gmail.com>> wrote:
> >
> >     Hi,
> >
> >     On Mon, Apr 28, 2014 at 3:29 PM, David Cournapeau
> >     <cournape at gmail.com <mailto:cournape at gmail.com>> wrote:
> >     >
> >     >
> >     >
> >     > On Sun, Apr 27, 2014 at 11:50 PM, Matthew Brett
> >     <matthew.brett at gmail.com <mailto:matthew.brett at gmail.com>>
> >     > wrote:
> >     >>
> >     >> Aha,
> >     >>
> >     >> On Sun, Apr 27, 2014 at 3:19 PM, Matthew Brett
> >     <matthew.brett at gmail.com <mailto:matthew.brett at gmail.com>>
> >     >> wrote:
> >     >> > Hi,
> >     >> >
> >     >> > On Sun, Apr 27, 2014 at 3:06 PM, Carl Kleffner
> >     <cmkleffner at gmail.com <mailto:cmkleffner at gmail.com>>
> >     >> > wrote:
> >     >> >> A possible option is to install the toolchain inside
> >     site-packages and
> >     >> >> to
> >     >> >> deploy it as PYPI wheel or wininst packages. The PATH to the
> >     toolchain
> >     >> >> could
> >     >> >> be extended during import of the package. But I have no idea,
> >     whats the
> >     >> >> best
> >     >> >> strategy to additionaly install ATLAS or other third party
> >     libraries.
> >     >> >
> >     >> > Maybe we could provide ATLAS binaries for 32 / 64 bit as part
> >     of the
> >     >> > devkit package.  It sounds like OpenBLAS will be much easier to
> >     build,
> >     >> > so we could start with ATLAS binaries as a default, expecting
> >     OpenBLAS
> >     >> > to be built more often with the toolchain.  I think that's how
> >     numpy
> >     >> > binary installers are built at the moment - using old binary
> >     builds of
> >     >> > ATLAS.
> >     >> >
> >     >> > I'm happy to provide the builds of ATLAS - e.g. here:
> >     >> >
> >     >> > https://nipy.bic.berkeley.edu/scipy_installers/atlas_builds
> >     >>
> >     >> I just found the official numpy binary builds of ATLAS:
> >     >>
> >     >> https://github.com/numpy/vendor/tree/master/binaries
> >     >>
> >     >> But - they are from an old version of ATLAS / Lapack, and only
> >     for 32-bit.
> >     >>
> >     >> David - what say we update these to latest ATLAS stable?
> >     >
> >     >
> >     > Fine by me (not that you need my approval !).
> >     >
> >     > How easy is it to build ATLAS targetting a specific CPU these days
> >     ? I think
> >     > we need to at least support nosse and sse2 and above.
> >
> >     I'm getting crashes trying to build SSE2-only ATLAS on 32-bits, I
> >     think Clint will have some time to help out next week.
> >
> >     I did some analysis of SSE2 prevalence here:
> >
> >     https://github.com/numpy/numpy/wiki/Window-versions
> >
> >     Firefox crash reports now have about 1 percent of machines without
> >     SSE2.  I suspect that people running new installs of numpy will have
> >     slightly better machines on average than Firefox users, but it's only
> >     a guess.
> >
> >     I wonder if we could add a CPU check on numpy import to give a polite
> >     'install from the exe' message for people without SSE2.
> >
> >
> > We could, although you unfortunately can't do it easily from ctypes only
> > (as you need some ASM).
> >
> > I can take a quick look at a simple cython extension that could be
> > imported before anything else, and would raise an ImportError if the
> > wrong arch is detected.
> >
>
> assuming mingw is new enough
>
> #ifdef __SSE2___
> raise_if(!__builtin_cpu_supports("sse"))
> #endof
>

We need to support it for VS as well, but it looks like win32 API has a
function to do it:
http://msdn.microsoft.com/en-us/library/ms724482%28VS.85%29.aspx

Makes it even easier.

David

>
> in import_array() should do it
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