Imperial College London
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Professor Peter Vincent

Faculty of Engineering, Department of Aeronautics

Professor of Computational Fluid Dynamics
 
 
 
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Contact

 

+44 (0)20 7594 1975p.vincent

 
 
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Location

 

211City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Vincent:2015,
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}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - 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 (www.pyfr.org).
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  -
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