Portable randomized list ranking on multiprocessors using MPI

  • Jesper Larsson Träff
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1497)

Abstract

We describe a simple multiprocessor list ranking algorithm with low communication volume and simple communication pattern. With p processors the algorithm performs < 4p (pipelined) communication rounds involving only point-to-point communication. For lists with N elements the algorithm runs in O(N ln p/p+p) time. Experiments with an implementation using MPI on a network of workstations and an IBM SP-2 comparing the algorithm to the well-known pointer jumping algorithm are reported. On the NOW the new algorithm is significantly better than pointer jumping. On the IBM SP-2 only the new algorithm was able to produce (modest) speed-up.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    F. Dehne and S. W. Song. Randomized parallel list ranking for distributed memory multiprocessors. International Journal of Parallel Programming, 25(1):1–16, 1997.MATHGoogle Scholar
  2. 2.
    A. Geist, A. Beguein, J. Dongarra, W. Jiang, R. Manchek, and V. Sunderam. PVM: Parallel Virtual Machine — A User's Guide and Tutorial for Networked Parallel Computing. MIT Press, 1994.Google Scholar
  3. 3.
    T.-S. Hsu and V. Ramachandran. Efficient massively parallel implementation of some combinatorial algorithms. Theoretical Computer Science, 162(2):297–322, 1996.MATHMathSciNetCrossRefGoogle Scholar
  4. 4.
    J. JáJá. An Introduction to Parallel Algorithms. Addison-Wesley, 1992.Google Scholar
  5. 5.
    W. F. McColl. Scalable computing. In Computer Science Today. Recent Trends and Developments, volume 1000 of Lecture Notes in Computer Science, pages 46–61, 1995.CrossRefGoogle Scholar
  6. 6.
    J. N. Patel, A. A. Khokhar, and L. H. Jamieson. Scalable parallel implementations of list ranking on fine-grained machines. IEEE Transactions on Parallel and Distributed Systems, 8(10):1006–1018, 1997.CrossRefGoogle Scholar
  7. 7.
    M. Reid-Miller. List ranking and list scan on the cray C-90. In Proceedings of the 6th ACM Symposium on Parallel Algorithms and Architectures (SPAA), pages 104–113, 1994.Google Scholar
  8. 8.
    J. F. Sibeyn. From parallel to external list ranking. Technical Report MPI-I-91-1-021, Max-Planck Institut für Informatik, 1997.Google Scholar
  9. 9.
    J. F. Sibeyn, F. Guillaume, and T. Seidel. Practical parallel list ranking. In Solving Irregularly Structured Problems in Parallel (IRREGULAR'97), volume 1253 of Lecture Notes in Computer Science, pages 25–36, 1997.Google Scholar
  10. 10.
    M. Snir, S. W. Otto, S. Huss-Lederman, D. W. Walker, and J. Dongarra. MPI: The Complete Reference. MIT Press, 1996.Google Scholar
  11. 11.
    J. L. Träff. Parallel list ranking and other operations on lists. Technical Report SFB 124-D6 3/97, Universität des Saarlandes, Saarbrücken, Germany, Sonderforschungsbereich 124, VLSI Entwurfsmethoden und Parallelität, 1997. 69 Pages.Google Scholar
  12. 12.
    L. G. Valiant. A bridging model for parallel computation. Communications of the ACM, 33(8):103–111, 1990.CrossRefGoogle Scholar
  13. 13.
    J. C. Wyllie. The Complexity of Parallel Computation. PhD thesis, Computer Science Department. Cornell University, 1979. Technical Report TR-79-387.Google Scholar

Copyright information

© Springer-Verlag 1998

Authors and Affiliations

  • Jesper Larsson Träff
    • 1
  1. 1.Lehrstuhl für Effiziente AlgorithmenTechnische Universität MünchenMünchenGermany

Personalised recommendations