Direct numerical simulations of reacting flows with detailed chemistry using many-core/GPU acceleration
AuthorsHernandez Perez, Francisco
Lee, Bok Jik
Im, Hong G.
KAUST DepartmentClean Combustion Research Center
Computational Reacting Flow Laboratory (CRFL)
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
Online Publication Date2018-03-29
Print Publication Date2018-09
Permanent link to this recordhttp://hdl.handle.net/10754/627433
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AbstractA new direct numerical simulation (DNS) code for multi-component gaseous reacting flows has been developed at KAUST, with the state-of-the-art programming model for next generation high performance computing platforms. The code, named KAUST Adaptive Reacting Flows Solver (KARFS), employs the MPI+X programming, and relies on Kokkos for “X” for performance portability to multi-core, many-core and GPUs, providing innovative software development while maintaining backward compatibility with established parallel models and legacy code. The capability and potential of KARFS to perform DNS of reacting flows with large, detailed reaction mechanisms is demonstrated with various model problems involving ignition and turbulent flame propagations with varying degrees of chemical complexities.
CitationHernández Pérez FE, Mukhadiyev N, Xu X, Sow A, Lee BJ, et al. (2018) Direct numerical simulations of reacting flows with detailed chemistry using many-core/GPU acceleration. Computers & Fluids. Available: http://dx.doi.org/10.1016/j.compfluid.2018.03.074.
SponsorsThe research work was sponsored by King Abdullah University of Science and Technology (KAUST) and made use of the computer clusters at KAUST Supercomputing Laboratory (KSL), and resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. Bok Jik Lee was partly supported by Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Science and ICT (2017R1A2B4003327). The authors also thank Dr. Hatem Ltaief at KSL for his assistance with the MAGMA library.
JournalComputers & Fluids