A Wednesday 03 March 2010 15:31:29 Jesper Larsen escrigué:
Hi people,
I was wondering about the status of using the standard library multiprocessing module with numpy. I found a cookbook example last updated one year ago which states that:
"This page was obsolete as multiprocessing's internals have changed. More information will come shortly; a link to this page will then be added back to the Cookbook."
http://www.scipy.org/Cookbook/multiprocessing
I also found the code that used to be on this page in the cookbook but it does not work any more. So my question is:
Is it possible to use numpy arrays as shared arrays in an application using multiprocessing and how do you do it?
Yes, it is pretty easy if your problem can be vectorised. Just split your arrays in chunks and assign the computation of each chunk to a different process. I'm attaching a code that does this for computing a polynomial on a certain range. Here it is the output (for a dual-core processor): Serial computation... 10000000 0 Time elapsed in serial computation: 3.438 3333333 0 3333334 1 3333333 2 Time elapsed in parallel computation: 2.271 with 3 threads Speed-up: 1.51x -- Francesc Alted