On Thu, Feb 9, 2012 at 12:05 PM, Guido van Rossum <guido@python.org> wrote:
On Thu, Feb 9, 2012 at 10:57 AM, Sturla Molden <sturla@molden.no> wrote:
Yes or no... Python is used for parallel computing on the biggest supercomputers, monsters like Cray and IBM blue genes with tens of thousands of CPUs. But what really fails to scale is the Python module loader! For example it can take hours to "import numpy" for 30,000 Python processes on a blue gene. And yes, nobody would consider to use Java for such systems, even though Java does not have a GIL (well, theads do no matter that much on a cluster with distributed memory anyway). It is Python, C and Fortran that are popular. But that really disproves that Python sucks for big concurrency, except perhaps for the module loader.
I'm curious about the module loader problem. Did someone ever analyze the cause and come up with a fix? Is it the import lock? Maybe it's something for the bug tracker.
+1 -eric