Ok, trying ProcessIdScalars filter obliged me to see the results more in
details (with spreadsheet view).
My input : 50 blocks containing each 1 polydata constituted by 1
point and 1
vertex cell
With a single process :
I get 50 blocks containing 1 point and 1 vertex cell, with PID = 0,
block number = ( index of the block + 1 )
So it is OK
With MPI (2 processes) :
I get 50 blocks containing 2 points and 2 vertices cells, each with
strange block numbers :
block id 0 -> pt 1 has BN=2, pt 2 has BN=3
block id 1 -> BN=(5,6)
block id 2 -> BN=(8,9)
block id 3 -> BN=(11,12) and so on...
It seems :
BN for Point1 = ( ( BlockID + 1 ) * 3 ) - 1
BN for Point2 = ( BlockID + 1 ) * 3
Point 1 of a block has always PID=0 and point 2 PID=1
Maybe I made something wrong when generating my input (please find
attached
a zip) ?
Yves Rogez
IPAG
Institut de Planétologie et d'Astrophysique de Grenoble
Bat D de Physique - BP. 53 - 38041 Grenoble - FRANCE
tel : +33 (0)4 76 63 52 80
lab : +33 (0)4 76 63 52 89
Le 15/01/2013 16:25, Utkarsh Ayachit a écrit :
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
<yves.ro...@obs.ujf-grenoble.fr> 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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Yves Rogez
IPAG / CNRS
