Dear Patrick, unfortunately I have no solution for your problem, but I want to say that we run into the same problems at the moment with parallel ParaView to visualize big data sets. In sequential mode and with smaller datasets ParaView is more or less stable.
But when we switch to parallel mode, ParaView crashes a lot in our tests. We also see the strange behavior of ParaView to multiplicate the memory footprint of the data in parallel mode. As far as I know that depends on the reader (on the data format). The VTK legacy reader seems not to be able to distribute data parts to the ParaView processes, instead all processes read all data, which is really cumbersome for big data visualization. At the moment I really wonder what the best data format (reader) is to distribute big data equally on the paraview processes. (For structured and for unstructured data.) Hdf5/Xmdf? VTK XML? I hope that there is a solution, so that big data visualization on a visualization cluster is possible with ParaView for real world data :) . Regards, Herwig
but runing pvserver in parallel on the server does'nt. If I launch : mpirun -np 4 /share/apps/paraView-server-3.08.1/bin/pvserver (with or without --use-offscreen-rendering) it crashes after loading the datas, while rendering (I think). On the client the message is: ERROR: In /home/utkarsh/Dashboards/MyTests/NightlyMaster/ParaViewSuperbuild-Release/paraview/src/paraview/VTK/Parallel/Core/vtkSocketCommunicator.cxx, line 812 vtkSocketCommunicator (0x177a380): Could not receive tag. 188969 On the server, the message is: mpirun noticed that process rank 2 with PID 25736 on node kareline exited on signal 9 (Killed). I also noticed some strange behavior: 1) after selecting the file to read and before clicking on the apply button, 3 of the 4 pvserver processes use 100% cpu. 2) after clicking the apply button, the 4 pvserver processes uses the same memory amount than the sequential run (8Gb each) So I think something is wrong in building my parallel version.
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