[Numpy-discussion] Objected-oriented SIMD API for Numpy

[Neal Becker]

...
> 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.
> 

I'm interested.  I'd like to try AMD rather than intel, because AMD is 
easier to obtain.  I'm running on intel machine, I hope that doesn't matter 
too much.

What exactly do I need to do?

I see that numpy/site.cfg has an MKL section.  I'm assuming I should not 
touch that, but just mess with gcc flags?