On Wed, Jan 29, 2014 at 10:52 PM, Donald Stufft <[email protected]> wrote:
> I don’t see any reason why SSE couldn’t be added as tags in the Wheel > filename fwiw. > You still need to decide when to install what, but I would be interested in talking more about that part. > > That doesn’t help for things like MKL though. > Nope, but MKL is actually easy in the sense that it deals with architectures at runtime. OSS numerical libraries generally don't (lots of work, and often a non issue when you can build stuff by yourself :) ). David > > On Jan 29, 2014, at 5:50 PM, David Cournapeau <[email protected]> wrote: > > > > > On Wed, Jan 29, 2014 at 10:27 PM, Chris Barker <[email protected]>wrote: > >> On Wed, Jan 29, 2014 at 2:04 PM, David Cournapeau <[email protected]>wrote: >> >>> I think the SSE issue is a bit of a side discussion: most people who >>> care about performance already know how to install numpy. What we care >>> about here are people who don't care so much about fast eigenvalue >>> decomposition, but want to use e.g. pandas. Building numpy in a way that >>> supports every architecture is both doable and acceptable IMO. >>> >> >> Exactly -- I'm pretty sure SSE2 is being suggested because that's the >> lowest common denominator that we expect to see a lot of -- if their really >> are a lot of non-SSE-2 machines out there we could leave that off, too. >> > > The failure mode is fairly horrible though, and the gain is not that > substantial anyway compared to really optimized installation (MKL, etc... > as provided by Continuum or us). > > >> Building numpy wheels is not hard, we can do that fairly easily (I have >>> already done so several times, the hard parts have nothing to do with wheel >>> or even python, and are related to mingw issues on win 64 bits). >>> >> >> David, >> >> Where is numpy as with building "out of the box" with the python.orgbinary >> for Windows, and the "standard" MS compilers that are used with >> those builds. That used to be an easy "python setup.py install" away -- has >> that changed? If so, is this a known bug, or a known >> we-aren't-supporting-that? >> >> i.e. it would be nice if anyone setup to build C extensions could "just >> build numpy". >> > > This has always been possible, and if not, that's certainly considered as > a bug (I would be eager to fix). > > Numpy is actually fairly easy to build if you have a C Compiler (which is > the obvious pain point on windows). Scipy, and fortran is where things fall > apart. > > David > _______________________________________________ > Distutils-SIG maillist - [email protected] > https://mail.python.org/mailman/listinfo/distutils-sig > > > > ----------------- > Donald Stufft > PGP: 0x6E3CBCE93372DCFA // 7C6B 7C5D 5E2B 6356 A926 F04F 6E3C BCE9 3372 > DCFA > >
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