Optimizing and tuning the fast multipole method for state-of-the-art multicore architectures

Proceedings of the 2010 IEEE International Symposium on Parallel and Distributed Processing, IPDPS 2010

Volumn , Issue , 2010, Pages

  Chandramowlishwaran, Aparna ^a,b   Williams, Samuel ^a   Oliker, Leonid ^a   Lashuk, Ilya ^b   Biros, Georgec ^b   Vuduc, Richard ^b  

^a LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

^b Georgia Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BARCELONA; FAST MULTIPOLE METHOD; MULTI-CORE SYSTEMS; MULTICORE ARCHITECTURES; NUMERICAL APPROXIMATIONS; PARALLELIZATIONS; PERFORMANCE ENHANCEMENTS; POWER EFFICIENCY; SINGLE-NODE PERFORMANCE;

DATA STRUCTURES; DISTRIBUTED PARAMETER NETWORKS; MICROPROCESSOR CHIPS; OPTIMIZATION; SOFTWARE ARCHITECTURE;

TUNING;

EID: 77953980209     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IPDPS.2010.5470415     Document Type: Conference Paper

References (17)

1. P. Ajmera, R. Goradia, S. Chandran, and S. Aluru. Fast, parallel, GPU-based construction of space filling curves and octrees. In Proc. Symp. Interactive 3D Graphics (I3D), 2008. (poster).
2. N. Arora, A. Shringarpure, and R. Vuduc. Direct n-body kernels for multicore platforms. In Proc. Int'l. Conf. Par. Proc. (ICPP), Sep. 2009.
3. O. Coulaud, P. Fortin, and J. Roman. Hybrid MPI-thread parallelization of the fast multipole method. In Proc. IS- PDC, Hagenberg, Austria, 2007.
4. M. Frigo and S. G. Johnson. The design and implementation of FFTW3. Proc. IEEE, 93, 2005.
5. L. Greengard and V. Rokhlin. A fast algorithm for particle simulations. J. Comp. Phys., 73, 1987.
6. N. A. Gumerov and R. Duraiswami. Fast multipole methods on graphics processors. J. Comp. Phys., 227:8290-8313, 2008.
7. B. Hariharan and S. Aluru. Efficient parallel algorithms and software for compressed octrees with applications to hierarchical methods. Par. Co., 31(3-4):311-331, 2005.
8. J. Kurzak and B. M. Pettitt. Massively parallel implementation of a fast multipole method for distributed memory machines. J. Par. Distrib. Comput., 65:870-881, 2005.
9. I. Lashuk, A. Chandramowlishwaran, H. Langston, T.-A. Nguyen, R. Sampath, A. Shringarpure, R. Vuduc, L. Ying, D. Zorin, and G. Biros. A massively parallel adaptive fast multipole method on heterogeneous architectures. In Proc. SC, Nov. 2009. (to appear).
10. K. Nitadori, J. Makino, and P. Hut. Performance tuning of n-body codes on modern microprocessors: I. Direct integration with a Hermite scheme on ×86-64 architecture. New Astron., 12:169-181, 2006. arXiv:astro- ph/0511062v1.
11. S. Ogata, T. J. Campbell, R. K. Kalia, A. Nakano, P. Vashishta, and S. Vemparala. Scalable and portable implementation of the fast multipole method on parallel comptuers. Computer Phys. Comm., 153(3):445-461, July 2003.
12. J. C. Phillips, J. E. Stone, and K. Schulten. Adapting a message-driven parallel application to GPU-accelerated clusters. In Proc. SC, 2008.
13. H. Sundar, R. S. Sampath, and G. Biros. Bottom-up construction and 2:1 balance refinement of linear octrees in parallel. SIAM J. Sci. Comput., 30(5):2675-2708, 2008.
14. M. S. Warren and J. K. Salmon. A parallel hashed octtree n-body algorithm. In Proc. SC, 1993.
15. L. Ying, G. Biros, D. Zorin, and H. Langston. A new parallel kernel-independent fast multipole method. In Proc. SC, 2003.
16. L. Ying, D. Zorin, and G. Biros. A kernel-independent adaptive fast multipole method in two and three dimensions. J. Comp. Phys., 196:591-626, May 2004.
17. Y. Zhong, M. Orlovich, X. Shen, and C. Ding. Array regrouping and structure splitting using whole-program reference affinity. ACM SIGPLAN Notices, 39(6):255-266, May 2004.