Imperial College London

Professor Peter Vincent

Faculty of EngineeringDepartment of Aeronautics

Professor of Computational Fluid Dynamics



+44 (0)20 7594 1975p.vincent




211City and Guilds BuildingSouth Kensington Campus






BibTex format

author = {Vincent, PE and Witherden, FD and Farrington, AM and Ntemos, G and Vermeire, BC and Park, JS and Iyer, AS},
title = {PyFR: Next-generation high-order computational fluid dynamics on many-core hardware},
year = {2015}

RIS format (EndNote, RefMan)

AB - © 2015, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. High-order numerical methods for unstructured grids combine the superior accuracy of high-order spectral or finite difference methods with the geometric flexibility of low-order finite volume or finite element schemes. The Flux Reconstruction (FR) approach unifles various high-order schemes for unstructured grids within a single framework. Additionally, the FR approach exhibits a signiflcant degree of element locality, and is thus able to run efflciently on modern many-core hardware platforms, such as Graphical Processing Units (GPUs). The aforementioned properties of FR mean it offers a promising route to per-forming affordable, and hence industrially relevant, scale-resolving simulations of hitherto intractable unsteady flows within the vicinity of real-world engineering geometries. Here we present PyFR, an open-source Python based framework for solving advection-diffusion type problems using the FR approach. 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 a custom Mako-derived domain specific language. Specifically, the current release of PyFR is able to solve the compressible Euler and Navier-Stokes equations on grids of quadrilateral and triangular elements in two dimensions, and hexahedral, tetrahedral, prismatic, and pyramidal elements in three dimensions, targeting clusters of multi-core CPUs, NVIDIA GPUs (K20, K40 etc.), AMD GPUs (S10000, W9100 etc.), and heterogeneous mixtures thereof. Results will be presented for various benchmark and real-world' flow problems. PyFR is freely available under an open-source 3-Clause New-Style BSD license (
AU - Vincent,PE
AU - Witherden,FD
AU - Farrington,AM
AU - Ntemos,G
AU - Vermeire,BC
AU - Park,JS
AU - Iyer,AS
PY - 2015///
TI - PyFR: Next-generation high-order computational fluid dynamics on many-core hardware
ER -