Tom Pinckney wrote:
All the discussion recently about pyprocessing got me interested in
actually benchmarking Python's multiprocessing performance to see if
reality matched my expectations around what would scale up and what
would not. I knew Python threads wouldn't be good for compute bound
problems, but I was curious to see how well they worked for i/o bound
problems. The short answer is that for i/o bound problems, python
threads worked just as well as using multiple operating system processes.
Interesting - given that your example compute bound problem happened to
be a matrix multiply, I'd be curious what the results are when using
python threads with numpy to do the same thing (my understanding is that
numpy will usually release the GIL while doing serious number-crunching)
Cheers,
Nick.
--
Nick Coghlan | [EMAIL PROTECTED] | Brisbane, Australia
---------------------------------------------------------------
http://www.boredomandlaziness.org
_______________________________________________
Python-Dev mailing list
[email protected]
http://mail.python.org/mailman/listinfo/python-dev
Unsubscribe:
http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
