10518

Accelerating moderately stiff chemical kinetics in reactive-flow simulations using GPUs

Kyle E Niemeyer, Chih-Jen Sung
Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
arXiv:1309.2710 [physics.comp-ph], (11 Sep 2013)

@article{2013arXiv1309.2710N,

   author={Niemeyer}, K.~E and {Sung}, C.-J.},

   title={"{Accelerating moderately stiff chemical kinetics in reactive-flow simulations using GPUs}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1309.2710},

   primaryClass={"physics.comp-ph"},

   keywords={Physics – Computational Physics, 80A32 (Primary) 80A30, 65L04, 65L06 (Secondary)},

   year={2013},

   month={sep},

   adsurl={http://adsabs.harvard.edu/abs/2013arXiv1309.2710N},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

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The chemical kinetics ODEs arising from operator-split reactive-flow simulations were solved on GPUs using explicit integration algorithms. Nonstiff chemical kinetics of a hydrogen oxidation mechanism (9 species and 38 irreversible reactions) were computed using the explicit fifth-order Runge-Kutta-Cash-Karp method, and the GPU-accelerated version performed faster than single- and six-core CPU versions by factors of 126 and 25, respectively, for 524,288 ODEs. Moderately stiff kinetics, represented with mechanisms for hydrogen/carbon-monoxide (13 species and 54 irreversible reactions) and methane (53 species and 634 irreversible reactions) oxidation, were computed using the stabilized explicit second-order Runge-Kutta-Chebyshev (RKC) algorithm. The GPU-based RKC implementation demonstrated an increase in performance of nearly 59 and 10 times, for problem sizes consisting of 262,144 ODEs and larger, than the single- and six-core CPU-based RKC algorithms using the hydrogen/carbon-monoxide mechanism. With the methane mechanism, RKC-GPU performed more than 65 and 11 times faster, for problem sizes consisting of 131,072 ODEs and larger, than the single- and six-core RKC-CPU versions, and up to 57 times faster than the six-core CPU-based implicit VODE algorithm on 65,536 ODEs. In the presence of more severe stiffness, such as ethylene oxidation (111 species and 1566 irreversible reactions), RKC-GPU performed more than 17 times faster than RKC-CPU on six cores for 32,768 ODEs and larger, and at best 4.5 times faster than VODE on six CPU cores for 65,536 ODEs. With a larger time step size, RKC-GPU performed at best 2.5 times slower than six-core VODE for 8192 ODEs and larger. Therefore, the need for developing new strategies for integrating stiff chemistry on GPUs was discussed.
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