skip to main content
10.1145/169627.169651acmconferencesArticle/Chapter ViewAbstractPublication PagesscConference Proceedingsconference-collections
Article
Free Access

A parallel adaptive fast multipole method

Authors Info & Claims
Published:01 December 1993Publication History
First page image

References

  1. 1.S.J. Aarseth, M. Henon, and R. Wielen. Astronomy and Astrophysics, 37, 1974.Google ScholarGoogle Scholar
  2. 2.Andrew A. Appel. An efficient program for many body simulation. SIAM Journal of Scient~c and Statistical Computing, 6:85-93, 1985.Google ScholarGoogle ScholarCross RefCross Ref
  3. 3.Joshua E. Barnes and Piet Hut. A hierarchical O(N log N) force calculation algorithm. Nature, 324(4):446--449, 1986.Google ScholarGoogle ScholarCross RefCross Ref
  4. 4.A. J. Chorin. Numerical study of slightly viscous flow. Journal of Fluid Mechanics, 57:785-796, 1973.Google ScholarGoogle ScholarCross RefCross Ref
  5. 5.Geoffrey C. Fox. Numerical Algorithms for Modern ParaUel Computer Architectures, chapter A Graphical Approach to Load Balancing and Sparse Matrix Vector Multiplication on the Hypercube, pages 37-62. Springer- Verlag, 1988.Google ScholarGoogle Scholar
  6. 6.Stephen R. Goldschmidt and Helen Davis. Tango introduction and tutorial. Technical Report CSL-TR-90-410, Stanford University, 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. 7.Leslie Greengard. The Rapid Evaluation of Potential Fields in Particle Systems. ACM Press, 1987.Google ScholarGoogle Scholar
  8. 8.Leslie Greengard and William Gropp. Parallel Processing for Scientific Computing, chapter A Parallel Version of the Fast Multipole Method, pages 213-222. SIAM, 1987. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. 9.Leslie Greengard and Vladimir Roldalin. A fast algorithm for particle simulation. Journal of Computational Physics, 73(325), 1987. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. 10.P. Hanrahan, D. Salzman, and L. Aupperle. A rapid hierarchical radiosity algorithm. In Proceedings of SIGGRAPH, 1991. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. 11.John L. Hennessy Jaswinder Pal Singh, Truman Joe and Anoop Gupta. An empirical comparison of the ksr-1 allcache and stanford dash multiprocessors. In Supercomputing '93, November 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. 12.Jacob Katzenelson. Computational structure of the N- body problem. SlAM Journal of Scientific and Statistical Computing, 10(4):787-815, 1989. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. 13.Dan Lenoski, James Laudon, Kourosh Gharachorloo, Anoop Gupta, and John Hennessy. The directory-based cache coherence protocol for the DASH multiprocessor. In Proceedings of the 17th Annual International Symposium on Computer Architecture, pages 148-159, May 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. 14.John K. Salmon. Parallel Hierarchical N-body Methods. PhD thesis, California Institute of Technology, December 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. 15.Jaswinder Pal Singh. Parallel Hierarchical N-body Methods and their Implications for Multiprocessors. PhD thesis, Stanford University, February 1993.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. 16.Jaswinder Pal Singh, Anoop Gupta, and John L. Hennessy. Implications of hierarchical N-body techniques for multiprocessor architecture. Submitted to A CM Transactions on Computer Systems. Early version available as Stanford Univeristy Tech. Report no. CSL-TR-92-506, January 1992. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. 17.Jaswinder Pal Singh and John L. Hennessy. High Performance Computing I!, chapter Data Locality and Memory System Performance in the Parallel Simulation of Ocean Eddy Currents, pages 43-58. North-Holland, 1991. Also Stanford University Tech. Report No. CSL-TR-91-490.Google ScholarGoogle Scholar
  18. 18.Jaswinder Pal Singh, Chris Holt, Takashi Totsuka, Anoop Gupta, and John L. Hennessy. Load balancing and data locality in hierarchical N-body methods. Journal of Parallel and Distributed Computing. To appear. Preliminary version available as Stanford Univeristy Tech. Report no. CSL-TR-92-505, January 1992.Google ScholarGoogle Scholar
  19. 19.Feng Zhao. An O(n) algorithm for three-dimensional N- body simulations. Technical Report 995, MIT Artificial Intelligence Laboratory, 1987. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. A parallel adaptive fast multipole method

            Recommendations

            Comments

            Login options

            Check if you have access through your login credentials or your institution to get full access on this article.

            Sign in
            • Published in

              cover image ACM Conferences
              Supercomputing '93: Proceedings of the 1993 ACM/IEEE conference on Supercomputing
              December 1993
              935 pages
              ISBN:0818643404
              DOI:10.1145/169627

              Copyright © 1993 ACM

              Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

              Publisher

              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 1 December 1993

              Permissions

              Request permissions about this article.

              Request Permissions

              Check for updates

              Qualifiers

              • Article

              Acceptance Rates

              Supercomputing '93 Paper Acceptance Rate72of300submissions,24%Overall Acceptance Rate1,516of6,373submissions,24%

            PDF Format

            View or Download as a PDF file.

            PDF

            eReader

            View online with eReader.

            eReader