Latest News
PyFR used to Explore Fundamentals of Turbulence - Results from simulations with PyFR on Piz Daint have been used to identify eigenmodes of averaged small-amplitude perturbations to turbulent channel flow
Towards Green Aviation with Python at Petascale - Simulations with PyFR on Piz Daint and Titan shortlisted for 2016 Gordon Bell Prize
PyFR Paper Published in Computers and Fluids - Open-access paper details heterogeneous computing with PyFR on Intel/Nvidia/AMD platform
PyFR used as Benchmark at Fourth HPCAC-ISC Student Cluster Contest - Teams from across the world battled it out for best performance within 3kW power envelope
PyFR Paper Published in Computer Physics Communications - Open-access paper details methodology plus scaling on over 100 Nvidia M2090 GPUs
Leveraging Rescale for High-Order CFD Simulation - PyFR is now available in the cloud via Rescale - no hardware required
Overview
Functionality
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. It is also designed to target a range of hardware platforms via use of an in-built domain specific language derived from the Mako templating engine. The current release (PyFR 1.12.2) has the following capabilities:
- Governing Equations - Euler, Navier Stokes
- Dimensionality - 2D, 3D
- Element Types - Triangles, Quadrilaterals, Hexahedra, Prisms, Tetrahedra, Pyramids
- Platforms - CPU Clusters, Nvidia GPU Clusters, AMD GPU Clusters
- Spatial Discretisation - High-Order Flux Reconstruction
- Temporal Discretisation - Explicit and Implicit (via Dual Time-Stepping)
- Precision - Single, Double
- Mesh Files Imported - Gmsh (.msh)
- Solution Files Exported - Unstructured VTK (.vtu, .pvtu)
Download
The source code is available on Github.
Documentation
Documentation is available on Read the Docs.
Forum
You can post a question on our Discourse forum.
Funding
Development of PyFR is or has been supported by the Engineering and Physical Sciences Research Council, Innovate UK, the European Commission, BAE Systems, Airbus, and the Air Force Office of Scientific Research. We are also grateful for hardware donations from Nvidia, Intel, and AMD.
Cite
To cite PyFR, please reference the following paper: