Peter Soendergaard wrote:
Hello,
I just browsed over the archives for Numpy-discussion and saw this, and decided to sign up.
I work on the ATLAS-project http://math-atlas.sourceforge.net/ and we have had similar problems with gcc3.0 Gcc 3.0 has a completely new backend which produces much slower floating point code on i386 machines. It is most visible on the Athlon, but it also also shows on on P4 and PIII machines. We havn't yet figured out if there are some optimizations that can make this go away, but if you need performance stick with the old 2.95 release for now.
By the way, if you would like to use Atlas in NumPy (I don't know if you do it already) I might be of some help. There is c-interfaces to the BLAS bundled with ATLAS, supporting both row-major and column-major storage.
Cheers,
Peter.
FROM: Rob DATE: 09/04/2001 18:02:05 SUBJECT: [Numpy-discussion] Python and Numpy compiled on Athlon optimized gcc3.01
Just for kicks last night I installed gcc3.01 which claims to have Athlon optimization, ie. -march=athlon. I recompiled Python and Numpy, and then ran a big simulation. The new compiler ran 200 seconds slower than the old gcc2.95 with plain -march=pentium. I need to go to the gcc website and see just what optimization they are claiming. Maybe I should have also used -02. Rob.
-- The Numeric Python EM Project
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Hi Peter, great to know that I'm not alone. Maybe I can build an EM simulator using all integer math :). I think I mentioned this on the list before, but Win2k on my laptop (1Ghz) runs Numpy and Python faster than my 1.2Ghz Athlon DDR machine using FreeBSD :( Also, for reference, I have a 3DNow optimized MP3encoding program Gogo that encodes mp3's 10x faster on the athlon than Lame does on my FreeBSD system on the laptop. Go figure! -- The Numeric Python EM Project www.members.home.net/europax