On Thu, Aug 6, 2009 at 15:57, Sturla Molden<stu...@molden.no> wrote: > >> Now linear algebra or FFTs on a GPU would probably be a huge boon, >> I'll admit - especially if it's in the form of a drop-in replacement >> for the numpy or scipy versions. > > NumPy generate temporary arrays for expressions involving ndarrays. This > extra allocation and copying often takes more time than the computation. > With GPGPUs, we have to bus the data to and from VRAM as well. D. Knuth > quoted Hoare saying that "premature optimization is the root of all > evil." Optimizing computation when the bottleneck is memory is premature.
> It is possibly to create a superfast NumPy. But just plugging GPGPUs > into the current design would be premature. In NumPy's current state, > with mutable ndarrays and operators generating temporary arrays, there > is not much to gain from introducing GPGPUs. It would only be beneficial > in computationally demanding parts like FFTs and solvers for linear > algebra and differential equations. I believe that is exactly the point that Erik is making. :-) -- 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
