Hi Dave,
Thanks for the insight and great citation, thanks for pointing it out.
Burlen
David E DeMarle wrote:
This is what I was thinking of:
*Parallel Hierarchical Visualization of Large Time-varying 3D Vector
Fields*
*Hongfeng Yu, Chaoli Wang, Kwan-Liu Ma
*David E DeMarle
Kitware, Inc.
R&D Engineer
28 Corporate Drive
Clifton Park, NY 12065-8662
Phone: 518-371-3971 x109
On Tue, Aug 25, 2009 at 9:46 AM, David E DeMarle
<[email protected] <mailto:[email protected]>> wrote:
There was a paper at Super Computing last year (or maybe the year
before) about improved partitioning for stream tracing that would
probably help alot. Think of making a filter like D3 which moves
data around to repartition, such that the partitions take into
account the principle flow directions. That way particles stay
resident much more often. The upfront cost might be high to do the
repartition, but afterwards stream tracing would be faster.
David E DeMarle
Kitware, Inc.
R&D Engineer
28 Corporate Drive
Clifton Park, NY 12065-8662
Phone: 518-371-3971 x109
On Tue, Aug 25, 2009 at 4:42 AM, John Biddiscombe
<[email protected] <mailto:[email protected]>> wrote:
Burlen
I have had performance issues with the Distributed Stream
tracer, but in fact I found that in general, the problem of it
not being very well optimized for parallel operation was not
the main trouble. If you are using Unstructured Grids, and
they are large (in my case 20million cells in a block), then
the main time was taken by the building of cell links which
are used to FindCEll inwhich an integration point lies. I
modified the stream tracer interpolation to use a BSP tree (or
CellLocator) and found a huge improvement in execution time.
(minutes instead of hours).
Secondly. the parallelization of the stream tracer is an
inherent problem. One cannot integrate the streamline in block
2, until it has reached a boundary in block 1 - one must wait
until the streamling traverses one block before passing it to
the next. In actuality, the implementation could be improved
with more intelligent seeding and rending/receiving of
streamline seeds etc between iterations.
The Particle tracer code could be modifed to produce
streamlines in a serial or distributed manner and ought to
give a 'reasonably' optimal solution to the problem - but in
fact the chaps at kitware are at the moment (they tell me) in
the process of revamping the streamline code to make use of
CellLocators - and for this reason I recently committed my BSP
tree code.
Here's how to check your bottleneck.
Find a large StructuredGrid dataset which is loaded in
parallel. Generate streamlines. Time it. Convert the grdi to
UnstructuredGrid and do the same. If test 1 takes 1 minute and
test 2 1 hour, then it isn't the parallization that's the real
issue, but the grid being used.
JB
We've been using the distributed stream tracer to generate
100s-1000s of stream lines per time step. It's very slow,
and it doesn't scale at all. The class comments say as
much. I'm sure there is a reason why this implementation
was chosen. Is there something that generally prevents
real parallel implementation? Is there a better
implementation available out there?
There is this post a while back
http://www.paraview.org/pipermail/paraview/2009-July/012959.html
What's the status?
Thanks
Burlen
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