2011/3/24 Dmitrey <tm...@ukr.net>: > Are there any plans for merging bottleneck into numpy?
No plans, but no particular opposition. bottleneck is a good place to experiment with these optimizations. When they settle, it might be worth folding them back in. > Also, are those benchmarks valid for ordinary numpy only or numpy with > MKL/ACML or it doesn't matter? Doesn't matter. > If I have huge arrays and multicore CPU, will numpy with MKL/ACML or > something else involve parallel computations with numpy funcs like amin, > amax, argmin, nanargmin etc? No. MKL/ACML focus on parallelizing expensive computation like matrix-matrix multiplication, not things like finding the minimum elements of an array. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
