<snip> > with "gcc -O3 -ffast-math -march=native -mfpmath=sse" optimizations > for the C code (involving SSE2 vectorization and whatnot, looking at > the assembler output). Numpy is already going essentially at the maximum > speed.
As a related side question that I've been wondering myself for some time already: what is the preferred way to compile numpy/scipy with those gcc optimization flags? Afaik, numpy's setup.py is simply picking up the flags that my distro's python was compiled with... Would the best way be to recompile python myself? Or could I fine-tune the gcc options just for numpy/scipy somehow? Vincent. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
