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 | ncoghlan at gmail.com | Brisbane, Australia
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