research-article

Parallel integration of planetary systems on GPUs

Authors:

Jianwei Gao,

Eric Ford,

Jörg PetersAuthors Info & Claims

ACMSE '08: Proceedings of the 46th annual ACM Southeast Conference

Pages 69 - 73

https://doi.org/10.1145/1593105.1593123

Published: 28 March 2008 Publication History

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Abstract

Direct numerical simulations of large numbers of planetary systems are key to the study extrasolar planetary systems. We investigate the potential of Graphics Processing Units (GPUs) to dramatically accelerate such calculations and enable new types of analyses. Here we report on a CUDA implementation of two different integrators, Verlet and Bulirsch-Stoer; that is, we are contrasting the relative efficiency of a low-memory-footprint, small-time-steps integrator with a more complex but highly stable integrator for best use of GPU resources.

We verify that GPUs can serve as highly efficient dedicated parallel computing co-processors of the CPU host: the wall-clock time of integrating a large number of systems is reduced by two orders of magnitude compared to a comparable implementation we used so far on a modern CPU. We verify further that it is not only possible to port a complex integration algorithm like Bulirsch-Stoer to the restrictive GPU environment but that it can outperform the simpler Verlet integrator.

References

[1]

R. Bulirsch and J. Stoer. Introduction to Numerical Analysis (Texts in Applied Mathematics, No 12). Springer, 1992.

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[2]

B. Leimkuhler and S. Reich. Simulating Hamiltonian Dynamics. Cambridge: Cambridge University Press, 2004.

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[3]

Peter Bodenheimer. Numerical Methods in Astrophysics: An Introduction(Astronomy and Astrophysics). Taylor & Francis, 2006.

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[4]

NVIDIA Corporation. NVIDIA CUDA Compute Unified Device Architecture Programming Guide 1.0, 2007.

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[5]

Hubert Nguyen. GPU Gem 3. Addison-Wesley Professional, 2007.

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Parallel integration of planetary systems on GPUs

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ACMSE '08: Proceedings of the 46th annual ACM Southeast Conference

March 2008

548 pages

ISBN:9781605581057

DOI:10.1145/1593105

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Association for Computing Machinery

New York, NY, United States

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Published: 28 March 2008

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ACM SE08

ACM SE08: ACM Southeast Regional Conference

March 28 - 29, 2008

Alabama, Auburn

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Best-effort semantic document search on GPUs

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