... > 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? _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
