4.5 Article

Direct numerical simulations of turbulent reacting flows with shock waves and stiff chemistry using many-core/GPU acceleration

Journal

COMPUTERS & FLUIDS
Volume 215, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compfluid.2020.104787

Keywords

Direct numerical simulation (DNS); WENO; GPU computing; High performance computing (HPC); Compressible turbulence; Performance analysis

Funding

  1. King Abdullah University of Science and Technology (KAUST)
  2. Office of Science of the U.S. Department of Energy [DE-AC0500OR22725]

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This paper presents the implementation of a seventh-order WENO7M scheme in the newly developed DNS code KARFS, accelerated by GPU computation. Performance characteristics and scalability are studied using different grid sizes and block decomposition, demonstrating the performance portability of KARFS on various architectures. The capability and potential of the newly implemented WENO7M scheme in KARFS to perform DNS of compressible flows are also demonstrated with model problems involving shocks, isotropic turbulence, detonations, and flame propagation into a stratified mixture with complex chemical kinetics.
Compressible reacting flows may display sharp spatial variation related to shocks, contact discontinuities or reactive zones embedded within relatively smooth regions. The presence of such phenomena emphasizes the relevance of shock-capturing schemes such as the weighted essentially non-oscillatory (WENO) scheme as an essential ingredient of the numerical solver. However, these schemes are complex and have more computational cost than the simple high-order compact or non-compact schemes. In this paper, we present the implementation of a seventh-order, minimally-dissipative mapped WENO (WENO7M) scheme in a newly developed direct numerical simulation (DNS) code called KAUST Adaptive Reactive Flows Solver (KARFS). In order to make efficient use of the computer resources and reduce the solution time, without compromising the resolution requirement, the WENO routines are accelerated via graphics processing unit (GPU) computation. The performance characteristics and scalability of the code are studied using different grid sizes and block decomposition. The performance portability of KARFS is demonstrated on a variety of architectures including NVIDIA Tesla P100 GPUs and NVIDIA Kepler K20X GPUs. In addition, the capability and potential of the newly implemented WENO7M scheme in KARFS to perform DNS of compressible flows is also demonstrated with model problems involving shocks, isotropic turbulence, detonations and flame propagation into a stratified mixture with complex chemical kinetics. (C) 2020 Elsevier Ltd. All rights reserved.

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