"Mathias" <[EMAIL PROTECTED]> wrote:
> I have a (pretty much) "emberassingly parallel" problem and look for the
> right toolbox to
> parallelize it over a cluster of homogenous linux workstations. I don't need
> automatic
> loop-parallelization or the like since I prefer to prepare the work packets
> "by hand".
> I simply need
> - to specify a list of clients
> - a means of sending a work packet to a free client and receiving the
> result (hopefully automatically without need to login to each one)
> - optionally a timeout mechanism if a client doesn't respond
> - optionally help for debugging of remote clients
>
> So far I've seen scipy's COW (cluster of workstation) package, but couldn't
> find documentation or
> even examples for it (and the small example in the code crashes...).
> I've noticed PYRO as well, but didn't look too far yet.
>
> Can someone recommend a parallelization approach? Are there examples or
> documentation? Has someone
> got experience with stability and efficiency?
googling for "parallel python" brings up lots of references; tools like
http://pympi.sourceforge.net/
http://datamining.anu.edu.au/~ole/pypar/
(see https://geodoc.uchicago.edu/climatewiki/DiscussPythonMPI for
a comparision)
seem to be commonly used.
</F>
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