<div dir="ltr"><p>Yes you generally still need MPI installed. You may also need to build paraview yourself.</p><p>At Kitware we inconsistently include MPI in our binaries due to technical difficulties regarding the range of OS's and versions we build for. Also, the MPI we distribute is likely not compatible and almost certainly not optimal on your hardware. Depending on your OS and distribution, there may be paraview-MPI package you can simply pull.</p>
<p style>And you are correct. Once you get paraview with mpi installed, run mpiexec -n N pvbatch to run it in parallel.</p><p style>See also: <a href="http://paraview.org/paraview/resources/webinars.html">http://paraview.org/paraview/resources/webinars.html</a> "Big Data Analysis" and <a href="http://extremecomputingtraining.anl.gov/files/2013/07/DOEPV.pdf">http://extremecomputingtraining.anl.gov/files/2013/07/DOEPV.pdf</a> for more background knowledge.</p>
<p style>On Jul 26, 2013 9:18 PM, "Nikolaos Beratlis" <<a href="mailto:nikos.beratlis@gmail.com" target="_blank">nikos.beratlis@gmail.com</a>> wrote:<br></p><p>
><br>
> I read in Paraview Wiki that as of Paraview 3.10 the MPI library is packaged in the binary release. Do I still need to have an MPI version installed on my computer to run Paraview in parallel in batch mode (pvbatch)? If MPI is not required, then how do I run pvbatch in parallel. Is there an argument to specify to use multi core on shared memory clusters? Otherwise I assume that a MPI version is required and I'd run it using "mpiexec -n Nprocs pvbatch python.py"<br>
><br>
> Thank you,<br>
><br>
> Nikos<br>
><br>
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