TY - GEN
T1 - Accelerating Euler equations numerical solver on graphics processing units
AU - Kestener, Pierre
AU - Château, Frédéric
AU - Teyssier, Romain
PY - 2010
Y1 - 2010
N2 - Finite volume numerical methods have been widely studied, implemented and parallelized on multiprocessor systems or on clusters. Modern graphics processing units (GPU) provide architectures and new programing models that enable to harness their large processing power and to design computational fluid dynamics simulations at both high performance and low cost. We report on solving the 2D compressible Euler equations on modern Graphics Processing Units (GPU) with high-resolution methods, i.e. able to handle complex situations involving shocks and discontinuities. We implement two different second order numerical schemes, a Godunov-based scheme with quasi-exact Riemann solver and a fully discrete second-order central scheme as originally proposed by Kurganov and Tadmor. Performance measurements show that these two numerical schemes can achieves x30 to x70 speed-up on recent GPU hardware compared to a mono-thread CPU reference implementation. These first results provide very promising perpectives for designing a GPU-based software framework for applications in computational astrophysics by further integrating MHD codes and N-body simulations.
AB - Finite volume numerical methods have been widely studied, implemented and parallelized on multiprocessor systems or on clusters. Modern graphics processing units (GPU) provide architectures and new programing models that enable to harness their large processing power and to design computational fluid dynamics simulations at both high performance and low cost. We report on solving the 2D compressible Euler equations on modern Graphics Processing Units (GPU) with high-resolution methods, i.e. able to handle complex situations involving shocks and discontinuities. We implement two different second order numerical schemes, a Godunov-based scheme with quasi-exact Riemann solver and a fully discrete second-order central scheme as originally proposed by Kurganov and Tadmor. Performance measurements show that these two numerical schemes can achieves x30 to x70 speed-up on recent GPU hardware compared to a mono-thread CPU reference implementation. These first results provide very promising perpectives for designing a GPU-based software framework for applications in computational astrophysics by further integrating MHD codes and N-body simulations.
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U2 - 10.1007/978-3-642-13136-3_29
DO - 10.1007/978-3-642-13136-3_29
M3 - Conference contribution
AN - SCOPUS:79956270006
SN - 3642131352
SN - 9783642131356
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 281
EP - 288
BT - Algorithms and Architectures for Parallel Processing - 10th International Conference, ICA3PP 2010, Workshops
T2 - 10th International Conference Algorithms and Architectures for Parallel Processing, ICA3PP 2010
Y2 - 21 May 2010 through 23 May 2010
ER -