# PyFR release: v1.15.0

**URL:** <https://pyfr.discourse.group/t/pyfr-release-v1-15-0/699>\
**Category:** News\
**Created:** [30 September 2022 22:40 UTC](https://pyfr.discourse.group/t/pyfr-release-v1-15-0/699 "2022-09-30T22:40:32Z")\
**Posts on this page:** 6\
**Page:** 1

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**Author:** ![p.vincent](https://yyz2.discourse-cdn.com/free1/user_avatar/pyfr.discourse.group/p.vincent/32/225_2.png) [@p.vincent](https://pyfr.discourse.group/u/p.vincent)\
**Post date:** [30 September 2022 22:40 UTC](https://pyfr.discourse.group/t/pyfr-release-v1-15-0/699/1 "2022-09-30T22:40:32Z")

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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.

Download:

> **[Release Release v1.15.0. · PyFR/PyFR](https://github.com/PyFR/PyFR/releases/tag/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 simulation...

Thanks again for your interest in the project.

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**Author:** ![fdw](https://avatars.discourse-cdn.com/v4/letter/f/a587f6/32.png) [@fdw](https://pyfr.discourse.group/u/fdw)\
**Post date:** [3 October 2022 15:29 UTC](https://pyfr.discourse.group/t/pyfr-release-v1-15-0/699/2 "2022-10-03T15:29:57Z")

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@mlaufer Are you okay to update the Spack packages?

Regards, Freddie.

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**Author:** ![mlaufer](https://yyz2.discourse-cdn.com/free1/user_avatar/pyfr.discourse.group/mlaufer/32/609_2.png) [@mlaufer](https://pyfr.discourse.group/u/mlaufer)\
**Post date:** [3 October 2022 18:00 UTC](https://pyfr.discourse.group/t/pyfr-release-v1-15-0/699/3 "2022-10-03T18:00:45Z")

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

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**Author:** ![fdw](https://avatars.discourse-cdn.com/v4/letter/f/a587f6/32.png) [@fdw](https://pyfr.discourse.group/u/fdw)\
**Post date:** [3 October 2022 22:17 UTC](https://pyfr.discourse.group/t/pyfr-release-v1-15-0/699/4 "2022-10-03T22:17:25Z")

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Great!

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.

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**Author:** ![luli](https://avatars.discourse-cdn.com/v4/letter/l/5f9b8f/32.png) [@luli](https://pyfr.discourse.group/u/luli)\
**Post date:** [10 October 2022 07:41 UTC](https://pyfr.discourse.group/t/pyfr-release-v1-15-0/699/5 "2022-10-10T07:41:57Z")

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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?

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**Author:** ![fdw](https://avatars.discourse-cdn.com/v4/letter/f/a587f6/32.png) [@fdw](https://pyfr.discourse.group/u/fdw)\
**Post date:** [10 October 2022 12:17 UTC](https://pyfr.discourse.group/t/pyfr-release-v1-15-0/699/6 "2022-10-10T12:17:01Z")

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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.