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Perhaps this will give you some useful pointers:
<a class="moz-txt-link-freetext" href="http://grasswiki.osgeo.org/wiki/Parallel_GRASS_jobs">http://grasswiki.osgeo.org/wiki/Parallel_GRASS_jobs</a><br>
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<div class="moz-cite-prefix">On 12/29/2012 01:03 PM, Paul Meems
wrote:<br>
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<div>Hi list,<br>
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Last night my test script successfully finished
processing my small area and created a annual
solar radiation raster.<br>
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I did a comparison with the solar radiation
produced by ArcMap and noticed its radiation is
almost twice as high as the one produced by Grass.
Probably I'm not using the correct output files.<br>
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I'm using glob_rad from r.sun as my result. I will
have a closer look why this difference is happening.<br>
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If anyone can give me some pointers that would be must
appreciated.<br>
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My real question today is how to speed up the process.
My script took 7 hours to finish, but only used a
fraction of the available resources. While running the
script (on Windows) only 30% of my quadcore CPU was used
and only 3GB of my 8GB RAM.<br>
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Since I'm looping on r.sun, calling it 365 times I was
thinking of calling it several times at once.<br>
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Is this possible? Calling r.sun 4 or 5 times at once will
decrease the time for the script to workable proportions.<br>
Probably this is more of a Python question than a GRASS
question but any pointers would be very helpful.<br>
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Thanks,<br>
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Paul<br>
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