Hi John,
In hind sight I think d3 is doing something reasonable. you have quite a
few use cases to support. when blocks are only a vehicle for
parallelism, the block structure doesn't matter and could be ignored or
done away with. when blocks describe physical structures, assemblies,
parts of a machines and so on, you will have to retain the full
heirarchy. perhaps a data partitioner could make a better decomposition
if there was a way to let the user choose which level of structure he
wants to retain and do the best it can within that constraint...
In my case ParaView had saved unexpected sub-block partitions, 1 dataset
per rank within each block, in the vtm file based on how many ranks were
running at the time i extracted the surface (8 ranks x 8 blocks = 64 sub
block partitions in the vtm file). But when that file is loaded in PV it
shows no evidence of this, both composite index and process id
correspond to the original 8 blocks. However d3 partitioned each of
those sub-block partitions. in my case 4 ranks 64 sub blocks = 256
partitions in all! definitely not what I expected and I guess its a
worst case scenario for d3. I don't care about sub block partitioning
structure that PV used when I saved the data. But there's no way the
writer, reader, or d3 could know that.
Burlen
On 05/10/2013 02:06 PM, Biddiscombe, John A. wrote:
Burlen, Ken, List
**
*>*
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.
<
This is my own experience too.
Question: What would you like to see in the output
1)Existing behaviour, each block is partitioned separately, previous
multiblock structure is preserved
2)All blocks partitioned as a single block, no multiblock structure in
the output
3)All blocks partitioned as a single block, multiblock structure from
input regenerated based on a block Id assigned to each cell prior to
partitioning.
The reason I ask is because I'm working on a new partitioning class
and I have not yet handled multi-block datasets and I wonder what
ought to be done in this case. 3) seems ideal, but is a bit harder and
might use some intermediate memory that would be undesireable.
JB
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