[usker]

I was wondering if anyone tried to use Star-CD with ParaView for postprocessing?

Thanks

[olesen]

At the moment, the only reasonable path is to export the results as EnSight format, which is supported by paraview. You may need a somewhat newer paraview version (eg, from cvs) that has misc. bugfixes for the ensight reader.

[carl]

Hello together,

I am not sure if I am in the right thread here, nevertheless:

I try postprocessing a Star-CD Case (actually saved as Ensight data)
with paraview 3.8.0, and I want to make it compute in parallel. I have
paraview already compiled with MPI and MESA support.

In first experiements are done on a 2-Core machine, I got as far as
this:

- in Paraview, connect to server
- Server setup as follows:
localhost, port 11111
Command: "mpirun -np 2 pvserver (optional: --off-screen-rendering)"

This is starting the 2 extra windows with (or without, respectively) the
rendered image.

The paraview processing works allright, yet the performance of the
parallel job is not any faster than when I just use paraview on a
single core, rather slightly slower. Neither can I find a significant
influence of the openGL-rendering, OK, so maybe my case is too simple
for that:

Case 1
paraview only: avg. 16 sec. / frame


Case 2
paraview client, server on localhost, "mpirun -np 2 pvserver"
rendering via openGL:
avg. 17 sec. / frame


Case 3
paraview client, server on localhost, "mpirun -np 2 pvserver"
off-screen-rendering:
avg. 17 sec. / frame


time documentation was done by via "save animation" and comparing the
timestamps, so they round to seconds. The animation was 5 frames long,
time per frame did not vary more than one sec.



Ideas that I have so far:

- parellizing does not help in my specific case (2-stroke engine,
moving mesh, filters are: "Cell Data to Point Data", slices and
iso-Surfaces), so I should use another testcase?

- the ENSIGHT reader is not parallelized?

- on a 2-core machine, effects are too small to be visible?

- do I need to decompose the computation domain somehow to tell
paraview how to seperate the data for the parallelization?

- computation time is very small compared to the time to fetch data
from ram, and since both cpus rely in the same ram, there is nearly
no speed-up?

- the whole thing is not properly parallelized and effectively uses
only one thread?


Next Steps:
Concerning the parallelized reader, I have read somewhere that the
OpenFOAM reader in paraview 3.8.0 is parallelzied, so I will try at least an OpenFOAM case. Do I need a decomposed case, or can I just take any case and take advantage of some automatic parallelization nontheless?

Is there any possibility to do some profiling of Paraview, like logging
the time a filter is taking, so to see at least where paraview
is taking the most time?

am I missing something else? any comments?

Thanks! Carl

[rrschor]

Hello Carl,

Did you find any answer to your parallelization problem? I'm starting to try this method of post possessing the ES-ICE data with paraView too.

Best regards,

Roberto