[gmx-developers] Python interface for Gromacs
Sébastien Buchoux
sebastien.buchoux at u-picardie.fr
Thu Sep 9 13:13:33 CEST 2010
Hi,
On 09/09/2010 08:38 AM, David van der Spoel wrote:
> People in the Lindahl group are working on parallellizing analysis
> tools because they are quickly becoming the bottleneck. We run
> simulations of large systems on hundreds of processors, and due to
> checkpointing this can be done largely unattended. Analysis can take a
> lot of effort, both hardware (CPU, Disk) and organisational. I think
> the prime advantage of a scripting languagae like Python could be
> organisational.
From my experience, Python is too slow to really make analysis tools
(or any heavy computational work) on its own. But it can use C/C++ libs
like a charm... hence a Python interface! :)
> @portability: I have tried compiling numpy a few times on mac & linux
> without success. As long as numpy is not in the main python
> distribution it will not be useful...
Numpy compilation can indeed be... troublesome. but I don't think it is
mandatory.
From my experience, Numpy is great for pure Python programming so it
would be useful for a 100% Python analysis tool. But with the use of C
to do the hard work, the advantage a Numpy is pretty slim and I think
that new Python types defined within a C extension are more efficient
since they allow Python users to access C objects directly (given the
use of a descent interface).
This is specially true when dealing with already written C objects that
are very different from C numarrays (i.e. they would need to be
"translated" to Numpy arrays prior to use any of the Numpy routines).
IMHO, the #1 priority of Numpy is much more to ease life of pure Python
programmers than to be useful to C extension programmers.
Sébastien
--
Sébastien Buchoux, MC
UMR 6022 - Génie Enzymatique et Cellulaire / Enzyme and Cell Engineering
Université Picardie Jules Verne (UPJV)
33, rue Saint Leu, 80000 Amiens, France
tel: +33(0)3 22 82 74 73 - email: sebastien.buchoux[at]u-picardie.fr
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