From numpy mailing list today:


I once wrote a module that replaces the built in transcendental
functions of numpy by optimized versions from Intels vector math
library. If someone is interested, I can publish it. In my experience it
was of little use since real world problems are limited by memory
bandwidth. Therefore extending numexpr with optimized transcendental
functions was the better solution. Afterwards I discovered that I could
have saved the effort of the first approach since gcc is able to use
optimized functions from Intels vector math library or AMD's math core
library, see the doc's of -mveclibabi. You just need to recompile numpy
with proper compiler arguments.