[SciPy-user] optimizing numpy on Linux?
Sat May 17 20:48:22 CDT 2008
I'm going to be deploying an application that makes extensive use of
numpy and scipy on a custom-built quad core machine running Linux.
We're at the moment running Ubuntu Server edition.
I've installed atlas3-base and the header packages via apt, and am
about to start compiling numpy and scipy from source. The trouble is,
I'd like it to be as fast as humanly possible, and don't know the
first thing about tweaking a Linux system for that. Is it a matter of
compiling and installing an optimized BLAS "by hand"? Are there any
strategies for benchmarking a numpy install?
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