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GPU‐accelerated direct numerical simulations of decaying compressible turbulence employing a GKM‐based solver
Author(s) -
Parashar Nishant,
Srinivasan Balaji,
Sinha Sawan Suman,
Agarwal Manish
Publication year - 2016
Publication title -
international journal for numerical methods in fluids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 112
eISSN - 1097-0363
pISSN - 0271-2091
DOI - 10.1002/fld.4291
Subject(s) - mach number , solver , computational science , computer science , turbulence , computational fluid dynamics , compressible flow , direct numerical simulation , compressibility , cuda , speedup , robustness (evolution) , turbulence kinetic energy , computation , mathematics , parallel computing , algorithm , mechanics , physics , reynolds number , biochemistry , chemistry , gene , programming language
Summary Gas Kinetic Method‐based flow solvers have become popular in recent years owing to their robustness in simulating high Mach number compressible flows. We evaluate the performance of the newly developed analytical gas kinetic method (AGKM) by Xuan et al. in performing direct numerical simulation of canonical compressible turbulent flow on graphical processing unit (GPU)s. We find that for a range of turbulent Mach numbers, AGKM results shows excellent agreement with high order accurate results obtained with traditional Navier–Stokes solvers in terms of key turbulence statistics. Further, AGKM is found to be more efficient as compared with the traditional gas kinetic method for GPU implementation. We present a brief overview of the optimizations performed on NVIDIA K20 GPU and show that GPU optimizations boost the speedup up‐to 40 x as compared with single core CPU computations. Hence, AGKM can be used as an efficient method for performing fast and accurate direct numerical simulations of compressible turbulent flows on simple GPU‐based workstations. Copyright © 2016 John Wiley & Sons, Ltd.