Hi,

We currently do parallel execution of ArGIS geoprocessing tools,
although not yet with GDAL.  We use IPython to execute normal commands
in parallel.  IPython is a shell replacement that has parallel commands
that can be used from the shell or within code.  

The biggest difficulty I have found is using resources efficiently.  You
will inevitably hit a bottleneck of either cpu speed, disk bandwidth,
network bandwidth or memory.  It is worth spending some time thinking
about what resources a particular process will consume, and where
bottlenecks are likely to occur.  



-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of John Donovan
Sent: 12 June 2009 12:06
To: [email protected]
Subject: [gdal-dev] Distributed processing

Hi,
We currently have a stand-alone app that converts, mosaicks and scales
GDAL-supported images to a proprietary format. It works well, but we
handle tens of thousands of source files at a time, which can slow the
process down to a crawl.

So we're investigating parallelising this process over several machines,
and I was wondering if anyone has any experience of this that they'd be
willing to share? It's still early days yet, so we're open to all
suggestions.

Regards,
John Donovan - Programmer, Virtalis Ltd.

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