On Sun, Jun 14, 2009 at 14:31, Bryan Cole<br...@cole.uklinux.net> wrote: > I'm starting work on an application involving cpu-intensive data > processing using a quad-core PC. I've not worked with multi-core systems > previously and I'm wondering what is the best way to utilise the > hardware when working with numpy arrays. I think I'm going to use the > multiprocessing package, but what's the best way to pass arrays between > processes? > > I'm unsure of the relative merits of pipes vs shared mem. Unfortunately, > I don't have access to the quad-core machine to benchmark stuff right > now. Any advice would be appreciated.
You can see a previous discussion on scipy-user in February titled "shared memory machines" about using arrays backed by shared memory with multiprocessing. Particularly this message: http://mail.scipy.org/pipermail/scipy-user/2009-February/019935.html -- 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
