On Fri, May 23, 2014 at 2:41 AM, Matthew Brett <matthew.br...@gmail.com> wrote:
> Hi, > > On Fri, May 9, 2014 at 4:06 AM, David Cournapeau <courn...@gmail.com> > wrote: > > > > > > > > On Fri, May 9, 2014 at 11:49 AM, Julian Taylor > > <jtaylor.deb...@googlemail.com> wrote: > >> > >> 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 > > > > > > 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. > > Nice. So all we would need is something like: > > try: > from ctypes import windll, wintypes > except (ImportError, ValueError): > pass > else: > has_feature = windll.kernel32.IsProcessorFeaturePresent > has_feature.argtypes = [wintypes.DWORD] > if not has_feature(10): > msg = ("This version of numpy needs a CPU capable of SSE2, " > "but Windows says - not so.\n", > "Please reinstall numpy using a superpack installer") > raise RuntimeError(msg) > > At the top of numpy/__init__.py > > What would be the best way of including that code in the 32-bit wheel? > (The 64-bit wheel can depend on SSE2). > Maybe write a separate file `_check_win32_sse2.py.in`, and ensure that when you generate `_check_win32_sse2.py` from setup.py you only end up with the above code when you go through the if len(sys.argv) >= 2 and sys.argv[1] == 'bdist_wheel': branch. Ralf > > Cheers, > > Matthew > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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