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

@article{Vermeire:2017:10.1016/j.jcp.2016.12.049,
author = {Vermeire, BC and Witherden and Vincent, PE},
doi = {10.1016/j.jcp.2016.12.049},
journal = {Journal of Computational Physics},
pages = {497--521},
title = {On the utility of GPU accelerated high-order methods for unsteady flow simulations: a comparison with industry-standard tools},
url = {http://dx.doi.org/10.1016/j.jcp.2016.12.049},
volume = {334},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - First- and second-order accurate numerical methods, implemented forCPUs, underpin the majority of industrial CFD solvers. Whilst this technologyhas proven very successful at solving steady-state problems via aReynolds Averaged Navier-Stokes approach, its utility for undertaking scaleresolvingsimulations of unsteady flows is less clear. High-order methods forunstructured grids and GPU accelerators have been proposed as an enablingtechnology for unsteady scale-resolving simulations of flow over complexgeometries. In this study we systematically compare accuracy and cost ofthe high-order Flux Reconstruction solver PyFR running on GPUs and theindustry-standard solver STAR-CCM+ running on CPUs when applied to arange of unsteady flow problems. Specifically, we perform comparisons ofaccuracy and cost for isentropic vortex advection (EV), decay of the Taylor-Green vortex (TGV), turbulent flow over a circular cylinder, and turbulent flowover an SD7003 aerofoil. We consider two configurations of STAR-CCM+: asecond-order configuration, and a third-order configuration, where the latterwas recommended by CD-Adapco for more effective computation of unsteadyflow problems. Results from both PyFR and Star-CCM+ demonstrate thatthird-order schemes can be more accurate than second-order schemes for agiven cost e.g. going from second- to third-order, the PyFR simulations of theEV and TGV achieve 75x and 3x error reduction respectively for the same orreduced cost, and STAR-CCM+ simulations of the cylinder recovered wakestatistics significantly more accurately for only twice the cost. Moreover,advancing to higher-order schemes on GPUs with PyFR was found to offereven further accuracy vs. cost benefits relative to industry-standard tools.
AU  - Vermeire,BC
AU  - Witherden
AU  - Vincent,PE
DO  - 10.1016/j.jcp.2016.12.049
EP  - 521
PY  - 2017///
SN  - 0021-9991
SP  - 497
TI  - On the utility of GPU accelerated high-order methods for unsteady flow simulations: a comparison with industry-standard tools
T2  - Journal of Computational Physics
UR  - http://dx.doi.org/10.1016/j.jcp.2016.12.049
UR  - http://hdl.handle.net/10044/1/43590
VL  - 334
ER  -
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