[Paraview] Parallel Data Redistribution

[Biddiscombe, John A.]

Berk

The data will be UnstructuredGrid for now. Multiblock, but actually, I don't really care what each block is, only that I accept one block on each of N processes, split it into more pieces, and the next filter accepts one (or more if the numbers don't match up nicely) blocks and process them. The redistribution shouldn't care what data types, only how many blocks in and out.

Looking at RedistributePolyData makes me realize my initial idea is no good. In my mind I had a pipeline where multiblock datasets are passed down the pipeline and simply the number of pieces is manipulated to achieve what I wanted - but I see now that if I have M pieces downstream mapped upstream to N pieces, what will happen is the readers will be effectively duplicated and M/N readers will read the same pieces. I don't want this to happen as IO will be a big problem if readers read the same blocks M/N times. 
I was hoping there was a way of simply instructing the pipeline to manage the pieces, but I see now that this won't work, as there needs to be a specific Send from each N to their M/N receivers (because the data is physically in another process, so the pipeline can't see it). This is very annoying as there must be a class which already does this (block redistribution, rather than polygon level redistribution), and I would like it to be more 'pipeline integrated' so that the user doesn't have to explicitly send each time an algorithm needs it.

I'll go through RedistributePolyData in depth and see what I can pull out of it - please feel free to steer me towards another possibility :)

JB


> -----Original Message-----
> From: Berk Geveci [mailto:berk.geveci at kitware.com]
> Sent: 11 December 2009 16:09
> To: Biddiscombe, John A.
> Cc: paraview at paraview.org
> Subject: Re: [Paraview] Parallel Data Redistribution
> 
> What is the data type? vtkRedistributePolyData and its subclasses do
> this for polydata. It can do load balancing (where you can specify a
> weight for each processor) as well.
> 
> -berk
> 
> On Fri, Dec 11, 2009 at 9:59 AM, Biddiscombe, John A. <biddisco at cscs.ch>
> wrote:
> > I have a filter pipeline which reads N blocks from disk, this works fine
> on N processors.
> >
> > I now wish to subdivide those N blocks (using a custom filter) to produce
> new data which will consist of M blocks - where M >> N.
> >
> > I wish to run the algorithm on M processors and have the piece information
> transformed between the two filters (reader -> splitter), so that blocks are
> distributed correctly. The reader will Read N blocks (leaving M-N processes
> unoccupied), but the filter which splits them up needs to output a different
> number of pieces and have the full M processes receiving data.
> >
> > I have a reasonably good idea of how to implement this, but I'm wondering
> if any filters already do something similar. I will of course take apart the
> D3 filter for ideas, but I don't need to do a parallel spatial decomposition
> since my blocks are already discrete - I just want to redistribute the
> blocks around and more importantly change the numbers of them between
> filters.
> >
> > If anyone can suggest examples which do this already, please do
> >
> > Thanks
> >
> > JB
> >
> > --
> > 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
> >
> >
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