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ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities.

ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of exascale size as well as on laptops for smaller data.

For more information see

How to use 

We recommend using your local computer for graphics and Gadi for rendering back end (paraview server).

In order for this combination to work the versions of paraview on your local computer and on Gadi needs to be the same.


$ module avail paraview

to see what versions are available. We normally recommend using the latest version available. For example, to load the 5.8.0 version of ParaView use

$ module load paraview/5.8.0-mesa

For more details on using modules see our software applications guide.

Install the same version of paraview on your local computer (instructions are in the paraview web site).

Note that we have 3 types of paraview modules:

  • Paraview built with opengl library (for example, paraview/5.8.0). This can be used with X11 server to do the rendering on Gadi.
  • Paraview built with mesa library (for example, paraview/5.8.0-mesa).
  • Paraview built with NVIDIA EGL library and VISTRX (paraview/5.8.0-gpu). Can run in gpuvolta queue only.

We recommend starting with paraview-mesa build as it is the most tested. The GPU version is an experimental build, not well tested.

Steps needed to work with paraview-mesa and paraview graphics on your local computer

1) Start an interactive job on Gadi:

$ qsub -I -X -l walltime=1:00:00,mem=180GB,ncpus=48,jobfs=1GB,storage=scratch/<project_code>+gdata/<project_code>

2) When the job starts, start pvserver:

$ module load paraview/5.8.0-mesa
$ mpirun pvserver

The pvserver prints a connection message, for example:

Connection URLcs://gadi-cpu-clx-1234:11111
Accepting connection(s): gadi-cpu-clx-1234:11111

3) Create an ssh tunnel through Gadi login node running on your local computer:

$ ssh -L11111:gadi-cpu-clx-1234:11111

and login as usual.

4) Run paraview on your local computer:

Create a server called localhost:11111 and then connect to it.

Authors: Andrey Bliznyuk, Mohsin Ali
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