In article <[EMAIL PROTECTED]>, John Nagle <[EMAIL PROTECTED]> wrote: >Caleb Hattingh wrote: >> On Apr 21, 11:02 pm, [EMAIL PROTECTED] wrote: >> >>>Hi, >>>I am using Python Thread library for my parallel processing course >>>project. I am doing matrix convolution on a multi-processor machine >>>running Solaris. I just found out that no speed-up is obtained with >>>threading. It is probably because of something called GIL in Python. >>>How can I get around >>>that GIL and get speed-up? >>>Thanks in advance. >>>Daniel > > If you're actually doing the convolution in Python, you need >optimization before you need more CPUs. There's a numerics library >for Python called NumPy, but it doesn't have a convolution function, >although it has an FFT, which may be useful. > > But this is just homework. Do something reasonable and turn it >in. A high performance solution to this problem is probably more >work than it's worth. > > John Nagle
Along with the excellent advice given by Dennis, John, and the rest, please be aware that *process*-level parallelization of a problem sometimes is a benefit. As already recommended, <URL: http://wiki.python.org/moin/ParallelProcessing > touches on most of the pertinent concepts. -- http://mail.python.org/mailman/listinfo/python-list
