On Apr 21, 10:53 pm, Dennis Lee Bieber <[EMAIL PROTECTED]> wrote: > On 21 Apr 2007 14:02:12 -0700, [EMAIL PROTECTED] declaimed the > following in comp.lang.python: > > > 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? > > Threading in Python is optimized for I/O bound processing, wherein > the threads spend most of their lives sleeping (blocked waiting for some > I/O to complete, or some lock/event/condition to change state). It is > not optimized for parallel number crunching. > > Options: > > Don't use the common "CPython" (eg, the Python built from C-language > source using the C-runtime library). Jython (a version that runs on the > JVM, using Java libraries) may not be afflicted with the GIL. >
IronPython is *definitely* not restricted by the GIL. Fuzzyman http://www.voidspace.org.uk/ironpython/index.shtml -- http://mail.python.org/mailman/listinfo/python-list
