On 09.05.2014 12:42, David Cournapeau wrote:
>
>
>
> On Fri, May 9, 2014 at 1:51 AM, Matthew Brett <matthew.br...@gmail.com
> <mailto:matthew.br...@gmail.com>> wrote:
>
> Hi,
>
> On Mon, Apr 28, 2014 at 3:29 PM, David Cournapeau
> <courn...@gmail.com <mailto:courn...@gmail.com>> wrote:
> >
> >
> >
> > On Sun, Apr 27, 2014 at 11:50 PM, Matthew Brett
> <matthew.br...@gmail.com <mailto:matthew.br...@gmail.com>>
> > wrote:
> >>
> >> Aha,
> >>
> >> On Sun, Apr 27, 2014 at 3:19 PM, Matthew Brett
> <matthew.br...@gmail.com <mailto:matthew.br...@gmail.com>>
> >> wrote:
> >> > Hi,
> >> >
> >> > On Sun, Apr 27, 2014 at 3:06 PM, Carl Kleffner
> <cmkleff...@gmail.com <mailto:cmkleff...@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
in import_array() should do it
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