Just to make sure, your ParaView is built with MPI support enabled,
right? XMLMultiBlockDataReader does distribute the blocks to read
among the processes. Try apply a "ProcessIdScalars" filter in the
middle and then look at the ProcessId assigned to the blocks in the
data. They should show how the blocks were distributed.

Utkarsh

On Tue, Jan 15, 2013 at 7:20 AM, Yves Rogez
<[email protected]> wrote:
> Hello,
>
> I'm trying to parallelize a process using pvbatch and MPI, with MultiBlock
> data set; thus using the vtk composite pipeline.
> I made a sample python program that is representative of what I have to do :
>
> --------------------------------------------------------------------------------------------------
>
> from paraview.simple import *
>
> r = servermanager.sources.XMLMultiBlockDataReader()
> r.FileName = "input.vtm"
>
> # Defining a sample fake data processing
> nbTs = 1000
> ts = {}
> for tIndex in range( 0, nbTs ):
>     ts[tIndex] = servermanager.filters.Transform()
>     if tIndex == 0:
>         ts[tIndex].Input = r
>     else:
>         ts[tIndex].Input = ts[tIndex - 1]
>     ts[tIndex].Transform.Scale = [1.01,1.01,1.01]
>
> w = servermanager.writers.XMLMultiBlockDataWriter()
> w.Input = ts[nbTs - 1]
> w.FileName = "output.vtm"
>
> w.UpdatePipeline()
>
> --------------------------------------------------------------------------------------------------
>
> I launch that using "mpiexec -np 4 pvbatch myscript.py"
> All run well but I get a longer time using MPI than using only "pvbatch
> myscript.py".
>
> By monitoring RAM, I noticed that it seems the data is loaded on time by MPI
> process, and (maybe) all the MPI processes do exactly the same job,
> computing four times all the data.
>
> Why my blocks in MultiBlock data set aren't dispatched over the MPI
> processes ?
> What am I doing wrong ?
>
> Many thanks for any help,
>
> Yves
>
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