Home
Reading
Searching
Subscribe
Sponsors
Statistics
Posting
Contact
Spam
Lists
Links
About
Hosting
Filtering
Features Download
Marketing
Archives
FAQ
Blog
 
Gmane
From: Nadav Horesh <nadavh <at> visionsense.com>
Subject: Re: multiprocessing shared arrays and numpy
Newsgroups: gmane.comp.python.numeric.general
Date: Thursday 4th March 2010 13:06:34 UTC (over 6 years ago)
Extended module that I used for some useful work.
Comments:
  1. Sturla's module is better designed, but did not work with very large
(although sub GB) arrays
  2. Tested on 64 bit linux (amd64) + python-2.6.4 + numpy-1.4.0

  Nadav.


-----Original Message-----
From: [email protected] on behalf of Nadav Horesh
Sent: Thu 04-Mar-10 11:55
To: Discussion of Numerical Python
Subject: RE: [Numpy-discussion] multiprocessing shared arrays and numpy
 
Maybe the attached file can help. Adpted and tested on amd64 linux

  Nadav


-----Original Message-----
From: [email protected] on behalf of Nadav Horesh
Sent: Thu 04-Mar-10 10:54
To: Discussion of Numerical Python
Subject: Re: [Numpy-discussion] multiprocessing shared arrays and numpy
 
There is a work by Sturla Molden: look for multiprocessing-tutorial.pdf
and sharedmem-feb13-2009.zip. The tutorial includes what is dropped in
the cookbook page. I am into the same issue and going to test it today.

  Nadav


On Wed, 2010-03-03 at 15:31 +0100, Jesper Larsen wrote:
> 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?
> 
> Best regards,
> Jesper
> _______________________________________________
> NumPy-Discussion mailing list
> [email protected]
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________
NumPy-Discussion mailing list
[email protected]
http://mail.scipy.org/mailman/listinfo/numpy-discussion
 
CD: 4ms