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Fri May 16 14:20:02 CEST 2008 · https://mail.python.org/pipermail/python-dev/2008-May/079498.html

2008/5/16 Hrvoje Nikšić <hrvoje.niksic at avl.com>:

> On Fri, 2008-05-16 at 08:04 -0400, Tom Pinckney wrote:
> > Here's one example, albeit from a few years ago
> >
> > http://aspn.activestate.com/ASPN/Mail/Message/numpy-discussion/1625465
>
> Thanks for the pointer.  I'm not sure I fully understand Konrad Hinsen's
> concerns, but maybe the problem is that Numpy's "number-crunching" needs
> to call back into Python frequently.  The notion of "releasing the GIL
> for number-crunching" assumes that the code is structured like this:
>
> 1. code that works with python objects ...
> 2. acquire pointer to a C struct/array ...
> 3. release GIL
> 4. work with C objects ("crunch the numbers") without calling any Python
> code and without touching Python objects or refcounts
> 5. reacquire GIL
>
> If step 4 needs to call into Python frequently, then this strategy won't
> really work.
>

Hi,

The current version of Numpy releases as soon as possible the GIL. The usual
macros for starting and stopping a GIL release (as advertised in the
documentation) are present for every step 4 work, whenever is possible (for
instance it is the case for universal functions which are used in a lot of
numpy's functions).

Matthieu
-- 
French PhD student
Website : http://matthieu-brucher.developpez.com/
Blogs : http://matt.eifelle.com and http://blog.developpez.com/?blog=92
LinkedIn : http://www.linkedin.com/in/matthieubrucher
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[Python-Dev] Python parallel benchmark