[Numpy-discussion] passing arrays between processes

Bryan Cole bryan at cole.uklinux.net
Mon Jun 15 02:22:55 EDT 2009

On Sun, 2009-06-14 at 15:50 -0500, Robert Kern wrote:
> On Sun, Jun 14, 2009 at 14:31, Bryan Cole<bryan at cole.uklinux.net> wrote:
> > I'm starting work on an application involving cpu-intensive data
> > processing using a quad-core PC. I've not worked with multi-core systems
> > previously and I'm wondering what is the best way to utilise the
> > hardware when working with numpy arrays. I think I'm going to use the
> > multiprocessing package, but what's the best way to pass arrays between
> > processes?
> >
> > I'm unsure of the relative merits of pipes vs shared mem. Unfortunately,
> > I don't have access to the quad-core machine to benchmark stuff right
> > now. Any advice would be appreciated.
> You can see a previous discussion on scipy-user in February titled
> "shared memory machines" about using arrays backed by shared memory
> with multiprocessing. Particularly this message:
> http://mail.scipy.org/pipermail/scipy-user/2009-February/019935.html


Does Sturla's extension have any advantages over using a
multiprocessing.sharedctypes.RawArray accessed as a numpy view?


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