[Numpy-discussion] Changing the distributed binary for numpy 1.0.4 for windows ?

Fernando Perez fperez.net@gmail....
Tue Dec 11 00:16:37 CST 2007

On Dec 10, 2007 11:04 PM, David Cournapeau <cournape@gmail.com> wrote:
> On Dec 11, 2007 12:46 PM, Andrew Straw <strawman@astraw.com> wrote:
> > According to the QEMU website, QEMU does not (yet) emulate SSE on x86
> > target, so a Windows installation on a QEMU virtual machine may be a
> > good way to build binaries free of these issues.
> > http://fabrice.bellard.free.fr/qemu/qemu-tech.html
> I tried this, this does not work (it actually emulates SSE). I went
> further, and managed to disable SSE support in qemu...
> But again, what's the point:  it takes ages to compile (qemu without
> the hardware accelerator is slow, like ten times slower), and you will
> end up with a really bad atlas, since atlas optimizaton is entirely
> based on runtime timers, which do not make sense anymore.
> I mean, really, what's the point of doing all this compared to using
> blas/lapack from netlib ? In practice, is it really slower ? For what
> ? I know I don't care so much, and I am a heavy user of numpy.

For certain cases the difference can be pretty dramatic, but I think
there's a simple, reasonable solution that is likely to work: ship TWO
binaries of Numpy/Scipy each time:

1. {numpy,scipy}-reference: built with the reference blas from netlib,
no atlas, period.

2. {}-atlas: built with whatever the developers have at the time,
which will likely mean these days a core 2 duo with SSE2 support.
What hardware it was built on should be indicated, so people can at
least know this fact.

Just indicate that:

- The atlas version is likely faster, but fully unsupported and likely
to crash older platforms, no refunds.

- If you *really* care about performance, you should build Atlas
yourself or be 100% sure that you're using an Atlas built on the same
chip you're using, so the build-time timing and blocking choices are
actually meaningful.

That sounds like a reasonable bit of extra work (a lot easier than
building a run-time dynamic atlas) with a true payoff in terms of
stability.  No?



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