Abstract
This paper proposes an acceleration strategy for SPH on single-node multi-GPU platform. First the acceleration strategy for SPH on single-GPU is studied in conjunction with the characteristics of architecture. Then the changing pattern of SPH’s computation time has been discussed. Based on the fact that the changing pattern is rather slow, using a simple dynamic load balancing algorithm an acceptable load balance is obtained on multi-GPU. Finally, an almost linear speedup is achieved on multi-GPU by further optimizing dynamic load balancing algorithm and communication strategy among multiple GPUs
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Gingold, R.A., Monaghan, J.J.: Smoothed particle hydrodynamics: theory and application to non-spherical stars. Mon. Not. R. Astron. Soc. 181, 375–389 (1977)
Lucy, L.B.: A numerical approach to the testing of the fission hypothesis. Astron. J. 82, 1013–1024 (1977)
Dominguez, J.M., Crespo, A.J.C., et al.: Neighbour lists in smoothed particle hydrodynamics. International Journal for Numerical Methods in Fluids 67(12), 2026–2042 (2011)
Fleissner, F., Eberhard, P.: Parallel load-balanced simulation for short-range interaction particle methods with hierarchical particle grouping based on orthogonal recursive bisection. International Journal for Numerical Methods in Engineering 74(4), 531–553 (2011)
Amada, T., Imura, M., et al.: Partilce-based fluid simulation on GPU. In: ACM Workshop on General-Purpose Computing on Graphics Processors and SIGGRAPH (2004)
Harada, T., Koshizuka, S., et al.: Smoothed particle hydrodynamics on GPUs. In: Proceedings of Computer Graphics International (2007)
Herault, A., Bilotta, G., et al.: SPH on GPU with CUDA. Journal of Hydraulic Research 48(1, suppl. 1) (2010)
Simon Green: Particle Simulation using CUDA, http://www.dps.uibk.ac.at/~cosenza/teaching/gpu/nv_particles.pdf
Rustico, E., Bilotta, G., et al.: Smoothed particle hydrodynamics simulations on multi-GPU systems. In: 20th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2012, February 15-17 (2012)
Rustico, E., Bilotta, G., et al.: A journey from single-GPU to optimized multi-GPU SPH with CUDA. In: 7th SPHERIC Workshop (2012)
Dominguez, J.M., Crespo, A.J.C., et al.: New multi-GPU implementation for smoothed particle hydrodynamics on heterogeneous clusters. Computer Physics Communications (2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hu, L., Shen, X., Long, X. (2013). Research on SPH Parallel Acceleration Strategies for Multi-GPU Platform. In: Wu, C., Cohen, A. (eds) Advanced Parallel Processing Technologies. APPT 2013. Lecture Notes in Computer Science, vol 8299. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45293-2_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-45293-2_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-45292-5
Online ISBN: 978-3-642-45293-2
eBook Packages: Computer ScienceComputer Science (R0)