Explicit integration with GPU acceleration for large kinetic networks

We demonstrate the first implementation of recently-developed 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...

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Vydáno v:Journal of computational physics Ročník 302; s. 591 - 602
Hlavní autoři: Brock, Benjamin, Belt, Andrew, Billings, Jay Jay, Guidry, Mike
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Elsevier Inc 01.12.2015
Elsevier
Témata:
Acceleration
Algorithms
Combustion
Computation
Computer simulation
Joining
MATHEMATICS AND COMPUTING
Networks
Nucleosynthesis
Ordinary differential equations
Reaction kinetics
Reaction networks
Reactive flows
Stiffness
Supernovae
Ordinary differential equations
Stiffness
Combustion
Reaction networks
Nucleosynthesis
Reactive flows
ISSN:0021-9991, 1090-2716
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Shrnutí:We demonstrate the first implementation of recently-developed 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. This orders-of-magnitude 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.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
AC05-00OR22725; AC05-00OR22750
USDOE Office of Science (SC), Nuclear Physics (NP)
ISSN:0021-9991
1090-2716
DOI:10.1016/j.jcp.2015.09.013