• DocumentCode
    3630290
  • Title

    Merging Jacobi and Gauss-Seidel methods for solving Markov chains on computer clusters

  • Author

    Jaroslaw Bylina;Beata Bylina

  • Author_Institution
    Institute of Mathematics, Marie Curie-Sklodowska University, plac Marii Curie-Sk?odowskiej 5, 20-031 Lublin, Poland
  • fYear
    2008
  • Firstpage
    263
  • Lastpage
    268
  • Abstract
    The authors consider the use of the parallel iterative methods for solving large sparse linear equation systems resulting from Markov chains-on a computer cluster. A combination of Jacobi and Gauss-Seidel iterative methods is examined in a parallel version. Some results of experiments for sparse systems with over 3 times 107 equations and about 2 times 108 nonzeros which we obtained from a Markovian model of a congestion control mechanism are reported.
  • Keywords
    "Merging","Jacobian matrices","Gaussian processes","Iterative methods","Concurrent computing","Equations","State-space methods","Clustering algorithms","Iterative algorithms","Mathematics"
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology, 2008. IMCSIT 2008. International Multiconference on
  • Print_ISBN
    978-83-60810-14-9
  • Type

    conf

  • DOI
    10.1109/IMCSIT.2008.4747250
  • Filename
    4747250
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3630290