best way to use paraview for AWS EC2?


I am using AWS EC2 graphic instance (x32 CPU, 128GB RAM, 1 GPU) regularly for post processing of CFD (OpenFOAM) cases. We usually use NICE DCV to connect to the machine with GUI and from there open up a Paraview session. Despite having 32 cpus, 128GB RAM and a gpu, we sometimes struggle to load and/or work/render openfoam cases as it gets very slow. We usually work with 30-50 million cells cases.

So my question is what is the best setup for my case?

  • Enabling multicore support from setting?
  • Using Paraview Server and Client both on AWS EC2?
  • Using Paraview Server on AWS EC2 and Client on my laptop (x12 CPUS, 32GB RAM, 1 GPU)? Is there a way that my laptop gnpu/cpu can be shared to increase the efficiency of interacting with paraview?
  • Or if the current workflow is as efficient as we can get with this instance type.


Sina, I routinely work with 0.5 gigacell (tets,hexes) unstructured grid datasets on Ubuntu 20 core / 64gbyte machines - so a 30-50 million cell case looks modest in size to me. I enable SMP using TBB (VTK_SMP_IMPLEMENTATION_TYPE=TBB). It could be that a filter in your workflow is not behaving well - there are have been dramatic performance improvements made to VTK/PV in the last couple of years - but there are still filters that need improvement. Can you elaborate on your workflow, what filters are you using, and what looks to be the bottlenecks?

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