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Distributed RAM Source Support #4
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👍 This would ease omega-k data analysis a lot. |
I think that would be super awesome for hacking PIConGPU: init configurations, new solvers/methods/... or live visualisation with matplotlib/paraview |
This was referenced Aug 24, 2015
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We do need an additional data source: distributed RAM (on MPI nodes).
With that we could process the host-memory of, e.g., PIConGPU
FieldE
host-buffers live during a simulation that is controlled via the PIConGPU python bindings.example:
start sim for 1000 steps
sync all FieldE to host(s)
operate on all FieldE with pyDive
sync all FieldE values back to device(s)
of course, the same is necessary for
particle
data sources.The text was updated successfully, but these errors were encountered: