• DocumentCode
    2035016
  • Title

    Scalability of Parallel Algorithms for Matrix Multiplication

  • Author

    Gupta, Anshul ; Kumar, Vipin

  • Author_Institution
    University of Minnesota, USA
  • Volume
    3
  • fYear
    1993
  • fDate
    16-20 Aug. 1993
  • Firstpage
    115
  • Lastpage
    123
  • Abstract
    A number of parallel formulations of dense matrix multiplication algorithm have been developed. For arbitrarily large number of processors, any of these algorithms or their variants can provide near linear speedup for sufficiently large matrix sizes and none of the algorithms can be clearly claimed to be superior than the others. In this paper we analyze the performance and scalability of a number of parallel formulations of the matrix multiplication algorithm and predict the conditions under which each formulation is better than the others.
  • Keywords
    Algorithm design and analysis; Computer science; Concurrent computing; Hypercubes; Matrix decomposition; Parallel algorithms; Parallel processing; Performance analysis; Scalability; Sparse matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing, 1993. ICPP 1993. International Conference on
  • Conference_Location
    Syracuse, NY, USA
  • ISSN
    0190-3918
  • Print_ISBN
    0-8493-8983-6
  • Type

    conf

  • DOI
    10.1109/ICPP.1993.160
  • Filename
    4134256