[Numpy-discussion] The BLAS problem (was: Re: Wiki page for building numerical stuff on Windows)

Matthew Brett matthew.brett at gmail.com
Mon Apr 28 20:41:35 EDT 2014


On Mon, Apr 28, 2014 at 5:10 PM, Julian Taylor
<jtaylor.debian at googlemail.com> wrote:
> On 29.04.2014 02:05, Matthew Brett wrote:
>> Hi,
>> On Mon, Apr 28, 2014 at 4:30 PM, Nathaniel Smith <njs at pobox.com> wrote:
>>> On Mon, Apr 28, 2014 at 11:25 AM, Michael Lehn <michael.lehn at uni-ulm.de> wrote:
>>>> Am 11 Apr 2014 um 19:05 schrieb Sturla Molden <sturla.molden at gmail.com>:
>>>>> Sturla Molden <sturla.molden at gmail.com> wrote:
>>>>>> Making a totally new BLAS might seem like a crazy idea, but it might be the
>>>>>> best solution in the long run.
>>>>> To see if this can be done, I'll try to re-implement cblas_dgemm and then
>>>>> benchmark against MKL, Accelerate and OpenBLAS. If I can get the
>>>>> performance better than 75% of their speed, without any assembly or dark
>>>> So what percentage on performance did you achieve so far?
>>> I finally read this paper:
>>>    http://www.cs.utexas.edu/users/flame/pubs/blis2_toms_rev2.pdf
>>> and I have to say that I'm no longer so convinced that OpenBLAS is the
>>> right starting point. They make a compelling argument that BLIS *is*
>>> the cleaned up, maintainable, and yet still competitive
>>> reimplementation of GotoBLAS/OpenBLAS that we all want, and that
>>> getting there required a qualitative reorganization of the code (i.e.,
>>> very hard to do incrementally). But they've done it. And, I get the
>>> impression that the stuff they're missing -- threading, cross-platform
>>> build stuff, and runtime CPU adaptation -- is all pretty
>>> straightforward stuff that is only missing because no-one's gotten
>>> around to sitting down and implementing it. (In particular that paper
>>> does include impressive threading results; it sounds like given a
>>> decent thread pool library one could get competitive performance
>>> pretty trivially, it's just that they haven't been bothered yet to do
>>> thread pools properly or systematically test which of the pretty-good
>>> approaches to threading is "best". Which is important if your goal is
>>> to write papers about BLAS libraries but irrelevant to reaching
>>> minimal-viable-product stage.)
>>> It would be really interesting if someone were to try hacking simple
>>> runtime CPU detection into BLIS and see how far you could get -- right
>>> now they do kernel selection via the C preprocessor, but hacking in
>>> some function pointer thing instead would not be that hard I think. A
>>> maintainable library that builds on Linux/OSX/Windows, gets
>>> competitive performance on last-but-one generation x86-64 CPUs, and
>>> gets better-than-reference-BLAS performance everywhere else, would be
>>> a very very compelling product that I bet would quickly attract the
>>> necessary attention to make it competitive on all CPUs.
>> I wonder - is there anyone who might be able to do this work, if we
>> found funding for a couple of months to do it?
> On scipy-dev a interesting BLIS related message was posted recently:
> http://mail.scipy.org/pipermail/scipy-dev/2014-April/019790.html
> http://www.cs.utexas.edu/~flame/web/
> It seems some work of integrating BLIS into a proper BLAS/LAPACK library
> is already done.

Has anyone tried building scipy with libflame yet?



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