PyFR release: v1.15.0

Dear All,

We have released PyFR v1.15.0.

New Features:

  • Improved performance and scaling of CUDA backend.
  • Improved performance across all backends via revised GiMMiK kernels.
  • Support for detecting load imbalances for multi-rank simulations.
  • Support for heterogeneous CPUs in the OpenMP backend.


Thanks again for your interest in the project.

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@mlaufer Are you okay to update the Spack packages?

Regards, Freddie.

Yes I am on it. :slight_smile:
M1 Mac support through Spack is a bit troublesome but works with some workarounds.


Also, feel free to submit a PR to the main PyFR repository explaining how Spack can be used in the quick install guide.

Regards, Freddie.

This is really very awesome! I noticed that it got a new performance boost on the cuda backend of the program. I would like to know how this was achieved. How much of a performance improvement over the old version?

The potential for a performance boost comes from the use of new GiMMiK kernels. If you will see a benefit is very situational, although it can be as much as 20%.

Regards, Freddie.

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