Explicit integration with GPU acceleration for large kinetic networks
In this study, we demonstrate the first implementation of recentlydeveloped fast explicit kinetic integration algorithms on modern graphics processing unit (GPU) accelerators. Taking as a generic test case a Type Ia supernova explosion with an extremely stiff thermonuclear network having 150 isotopic species and 1604 reactions coupled to hydrodynamics using operator splitting, we demonstrate the capability to solve of order 100 realistic kinetic networks in parallel in the same time that standard implicit methods can solve a single such network on a CPU. In addition, this ordersofmagnitude decrease in computation time for solving systems of realistic kinetic networks implies that important coupled, multiphysics problems in various scientific and technical fields that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible.
 Authors:

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 Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)
 Publication Date:
 Grant/Contract Number:
 AC0500OR22725
 Type:
 Accepted Manuscript
 Journal Name:
 Journal of Computational Physics
 Additional Journal Information:
 Journal Volume: 302; Journal ID: ISSN 00219991
 Publisher:
 Elsevier
 Research Org:
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 Sponsoring Org:
 USDOE Office of Science (SC)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 97 MATHEMATICS AND COMPUTING; Ordinary differential equations; Reaction networks; Stiffness; Reactive flows; Nucleosynthesis; Combustion
 OSTI Identifier:
 1271855
 Alternate Identifier(s):
 OSTI ID: 1247036
Brock, Benjamin, Belt, Andrew, Billings, Jay Jay, and Guidry, Mike W. Explicit integration with GPU acceleration for large kinetic networks. United States: N. p.,
Web. doi:10.1016/j.jcp.2015.09.013.
Brock, Benjamin, Belt, Andrew, Billings, Jay Jay, & Guidry, Mike W. Explicit integration with GPU acceleration for large kinetic networks. United States. doi:10.1016/j.jcp.2015.09.013.
Brock, Benjamin, Belt, Andrew, Billings, Jay Jay, and Guidry, Mike W. 2015.
"Explicit integration with GPU acceleration for large kinetic networks". United States.
doi:10.1016/j.jcp.2015.09.013. https://www.osti.gov/servlets/purl/1271855.
@article{osti_1271855,
title = {Explicit integration with GPU acceleration for large kinetic networks},
author = {Brock, Benjamin and Belt, Andrew and Billings, Jay Jay and Guidry, Mike W.},
abstractNote = {In this study, we demonstrate the first implementation of recentlydeveloped fast explicit kinetic integration algorithms on modern graphics processing unit (GPU) accelerators. Taking as a generic test case a Type Ia supernova explosion with an extremely stiff thermonuclear network having 150 isotopic species and 1604 reactions coupled to hydrodynamics using operator splitting, we demonstrate the capability to solve of order 100 realistic kinetic networks in parallel in the same time that standard implicit methods can solve a single such network on a CPU. In addition, this ordersofmagnitude decrease in computation time for solving systems of realistic kinetic networks implies that important coupled, multiphysics problems in various scientific and technical fields that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible.},
doi = {10.1016/j.jcp.2015.09.013},
journal = {Journal of Computational Physics},
number = ,
volume = 302,
place = {United States},
year = {2015},
month = {9}
}