[Paraview] distributed stream tracer scalability issue

Tue Aug 25 10:24:28 EDT 2009

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
<dave.demarle at kitware.com>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 <biddisco at cscs.ch>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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>>
>>
>> --
>> John Biddiscombe,                            email:biddisco @ cscs.ch
>> http://www.cscs.ch/
>> CSCS, Swiss National Supercomputing Centre  | Tel:  +41 (91) 610.82.07
>> Via Cantonale, 6928 Manno, Switzerland      | Fax:  +41 (91) 610.82.82
>>
>>
>> _______________________________________________
>> Powered by www.kitware.com
>>
>> Visit other Kitware open-source projects at
>> http://www.kitware.com/opensource/opensource.html
>>
>> Please keep messages on-topic and check the ParaView Wiki at:
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>
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