• DocumentCode
    694339
  • Title

    Research on parallel model for sparse matrix-vector iterative multiplication

  • Author

    Jingzhu Li ; Peng Zou ; Qingbo Wu

  • Author_Institution
    Sch. of Comput. Sci., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2013
  • fDate
    12-13 Oct. 2013
  • Firstpage
    122
  • Lastpage
    125
  • Abstract
    The most effective algorithms of solving large sparse linear system are Block Wiedemann and Block Lanczos, sparse matrix-vector multiplication iterations is the main process of these algorithms, to achieve parallel computing of its process, we have established three different parallel algorithm models and analyzed the characteristic features of their computing and communication, and through the analysis and comparison of time-cost, we choose the optimal model.
  • Keywords
    iterative methods; linear systems; matrix multiplication; parallel algorithms; sparse matrices; vectors; Block Lanczos; Block Wiedemann; large sparse linear system; parallel algorithm model; parallel computing; sparse matrix-vector iterative multiplication; Computational modeling; Data models; Educational institutions; Load modeling; Mathematical model; Sparse matrices; Vectors; Block Lanczos; Block Wiedemann; Large sparse linear equations; Parallel Computing; sparse matrix-vector iterative multiplication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on
  • Conference_Location
    Dalian
  • Type

    conf

  • DOI
    10.1109/ICCSNT.2013.6967077
  • Filename
    6967077