PyFR is an open-source Python based framework for solving advection-diffusion type problems on streaming architectures using the Flux Reconstruction approach of Huynh. The framework is designed to solve a range of governing systems on mixed unstructured grids containing various element types. Support for AMD hardware has been integrated into the PyFR project and can be found at PyFR.org and PyFR GitHub.
This section describes how to launch the containers. It is assumed that up-to-versions of Docker and/or Singularity is installed on your system. If needed, please consult with your system administrator or view official documentation.
There are several PyFR examples in the PyFR Test Cases repo as well as a BSF, Naca0021, and TVG that PyFR supports. We have details for the latter.
Note: These benchmarks/examples prefer to be run in an interactive session, if the output is captured to a file, it will result in a single line with possibly hundreds of thousands of characters.
tail -c 80 <PyFR-example.log>should capture the last executed frame with the elapsed time. Depending on the size of the example, it may be a few characters off.
BSF
The script will make PyFR boot up the benchmark, compile the GPU kernels, and execute the simulation.
The user can track progress through a built-in progress bar in the application.
/examples/bsf/run_bsf
NOTE: It is not possible to run the BFS input set with more than one GPU currently.
TGV
The script converts the mesh to a PyFR mesh first and compiles the GPU kernels, and executes the simulation.
As a convenience, this is performed in the benchmark script which can be run using 1 or 2 GPUs.
Replace <NGPU> with the desired number of GPUs to use
/examples/tgv/run_tgv <NGPU>
NACA0021
The script extracts, then converts the mesh to a PyFR mesh first, for multiple GPU runs it will partition the mesh, then compiles the GPU kernels, and executes the simulation.
As a convenience, this is performed in the benchmark script which can be run using 1 to 8 GPUs.
Replace <NGPU> with the desired number of GPUs to use
/examples/naca0021/run_naca0021 <NGPU>
PyFR Test Cases
The PyFR test cases have been already provided into the container, they are located at /examples/PyFR-Test-Cases, These examples must be run interactively.
The instructions on how to run these test cases can be located at PyFr Examples.
NOTES:
- The examples use
cudabe sure to replace this withhipto run with AMD GPUs.- Paraview has not been included in the container
- Unstructured VTK (.vtu) files can be placed in a mounted directory to access them on host machine. See Docker or Singularity documentation for details on how to mount a directory into the container.
Your access and use of this application is subject to the terms of the applicable component-level license identified below. To the extent any subcomponent in this container requires an offer for corresponding source code, AMD hereby makes such an offer for corresponding source code form, which will be made available upon request. By accessing and using this application, you are agreeing to fully comply with the terms of this license. If you do not agree to the terms of this license, do not access or use this application.
The application is provided in a container image format that includes the following separate and independent components:
| Package | License | URL |
|---|---|---|
| Ubuntu | Creative Commons CC-BY-SA Version 3.0 UK License | Ubuntu Legal |
| CMAKE | OSI-approved BSD-3 clause | CMake License |
| OpenMPI | BSD 3-Clause | OpenMPI License OpenMPI Dependencies Licenses |
| OpenUCX | BSD 3-Clause | OpenUCX License |
| ROCm | Custom/MIT/Apache V2.0/UIUC OSL | ROCm Licensing Terms |
| PyFR | BSD-3 Clause | PyFR PyFR License |
| PyFR Test Cases | Creative Commons Attribution 4.0 | PyFR Test Cases License |
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