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<div>I am guessing that this has to do with the blocks in your multiblock dataset. The D3 filter will partition each block independently. This means that each process will have a small region in each partition, which will be spread throughout the dataset.</div>
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<div>Although not a good solution, one way around the problem would be to first run the merge blocks filters to construct a monolithic unstructured grid, and then run D3.</div>
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<div>-Ken</div>
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<span style="font-weight:bold">From: </span>Burlen Loring <<a href="mailto:bloring@lbl.gov">bloring@lbl.gov</a>><br>
<span style="font-weight:bold">Date: </span>Thursday, May 9, 2013 5:36 PM<br>
<span style="font-weight:bold">To: </span>"<a href="mailto:paraview@paraview.org">paraview@paraview.org</a>" <<a href="mailto:paraview@paraview.org">paraview@paraview.org</a>><br>
<span style="font-weight:bold">Subject: </span>[EXTERNAL] [Paraview] d3 poor domain decomposition<br>
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<div bgcolor="#FFFFFF" text="#000000">I wanted to report a situation where D3 is generating really poor domain decomposition. In this case it's taking decent data locality and destroying it. This is a multiblock with 8 polydata surfaces. Screen shot shows result
with 4 mpi ranks, 8 produces a similar result. D3 usually does a great job, so maybe this has hit some of its weak spots. I'm surprised that there are so many disconnected regions on each rank and that it doesn't retain any of the initial data locality. Although
here I was just experimenting trying to get a more even data distribution by using d3, I think similar use cases arise frequently. for example the need to re-balancing the data distribution after an iso-surface in parallel. Should this be considered a bug?<br>
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<img src="cid:part1.08060803.06010605@lbl.gov" alt=""><br>
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