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. In case it's relevant: the data takes the form of a stream of numpy.double arrays with sizes in the range 2000 to 10000. cheers, Bryan _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
