Is your NumPy using the right ATLAS?

Here's a tip I got from my colleague Martin. Making sure that your NumPy installation uses the right back-end can drastically improve performance. ATLAS is the software library used by NumPy (and Matlab, Octave etc.) to do linear algebra.

Try running the following 1000*1000 matrix multiplication test:

>>> from numpy import *
>>> import time
>>> A = random.random((1000,1000))
>>> B = random.random((1000,1000))
>>> t = time.time(); dot(A,B); print time.time()-t

Disappointed about the time this takes? Take a minute to check that you are running the right ATLAS for your computer. On my Mac this test was fast (0.2-0.3s) but on my desktop running Ubuntu very slow (5-6s). In Ubuntu, open the Package Manager and search for "atlas". If you find something like "libatlas3gf-base" you are using a generic version that works on most hardware. Unless your computer is antique, you can probably do better. Try selecting "libatlas3gf-sse2" (or even libatlas3gf-sse1 if this doesn't work) instead and run the test again. (on other linux platforms the process should be similar)

Tests I did on a couple of machines show speedup of a factor 4-10. Well worth the minute it takes to check and fix. Thanks Martin!