• DocumentCode
    238560
  • Title

    Multithreaded Direction Preserving Preconditioners

  • Author

    Kumar, Pranaw

  • Author_Institution
    Competence center for HPC, Fraunhofer ITWM, Kaiserslautern, Germany
  • fYear
    2014
  • fDate
    24-27 June 2014
  • Firstpage
    148
  • Lastpage
    155
  • Abstract
    The scalability and robustness of a class of nonoverlapping domain decomposition preconditioners using 2-way nested dissection reordering is studied. We consider two different factorizations: nested and block versions. Both these variants have advantages and disadvantages. The nested variants have less than half the memory requirements compared to block variants. On the other hand, the block variants have faster solve phase and converges within similar number of iterations. In particular, four methods are considered: a nested symmetric successive over relaxation (NSSOR), its block variant block SSOR (BSSOR), nested filtering factorization (NFF), and its block variant block filtering factorization (BFF). The recently introduced filtering preconditioners namely NFF and BFF are two filtering preconditioners that preserve direction on a given filter vector. The scalability and robustness of these methods are discussed on shared memory architecture. We outline the algorithmic differences between NFF and BFF. The implementation is recursive and cache oblivious. The test cases consist of a Poisson problem and convection-diffusion problems with jumping coefficients.
  • Keywords
    matrix decomposition; multi-threading; 2-way nested dissection reordering; NFF; Poisson problem; block SSOR; block factorization; block filtering factorization; convection-diffusion problem; jumping coefficients; memory requirements; multithreaded direction preserving preconditioners; nested factorization; nested filtering factorization; nested symmetric successive over relaxation; nonoverlapping domain decomposition preconditioners; Approximation methods; Binary trees; Particle separators; Partitioning algorithms; Robustness; Sparse matrices; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Computing (ISPDC), 2014 IEEE 13th International Symposium on
  • Conference_Location
    Marseilles
  • Print_ISBN
    978-1-4799-5918-1
  • Type

    conf

  • DOI
    10.1109/ISPDC.2014.23
  • Filename
    6900213