[Numpy-discussion] Fast threading solution thoughts
Thu Feb 12 08:34:58 CST 2009
David Cournapeau wrote:
> Matthieu Brucher wrote:
>> For BLAS level 3, the MKL is parallelized (so matrix multiplication is).
> Same for ATLAS: thread support is one focus in the 3.9 serie, currently
> in development.
ATLAS has had thread support for a long, long time. The 3.9 series just
improves it substantially by using affinity when available and removes
some long standing issues with allocation performance that one had to
work around before by setting some defines at compile time.
> I have never used it, I don't know how it compare to the
It does compare quite well and is more or less on par with the latest
MKL releases in the 3.9 series. 3.8.2 is maybe 10% to 15% slower on i7
as well as Core2 cores than the MKL. On big advantage of ATLAS is that
it tends to work when using it with numpy/scipy unlike the Intel MKL
where one has to work around a bunch of oddities and jump through hoops
to get it to work. It seems that Intel must rename at least one library
in each release of the MKL to keep build system maintainers occupied :)
The big disadvantage of ATLAS is that Windows support is currently
limited to 32 bits, but 3.9.5 and higher have SFU/SUA support, so 64 bit
support is possible. Clint told me the main issue here was lack of
access and it isn't too high on his priority list.
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