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Schwarz Methods: To Symmetrize or Not to Symmetrize

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اقرأ أكثر حفظ في قائمتي
  • نوع التسجيلة:
    Electronic Resource
  • الدخول الالكتروني :
    https://authors.library.caltech.edu/12608/
    https://resolver.caltech.edu/CaltechAUTHORS:HOLsiamjna97
    https://authors.library.caltech.edu/12608
    https://resolver.caltech.edu/CaltechAUTHORS:HOLsiamjna97
    CaltechAUTHORS:HOLsiamjna97
    10.1137/S0036142994275743
  • معلومة اضافية
    • Publisher Information:
      SIAM 1997-04
    • Added Details:
      Holst, Michael
      Vandewalle, Stefan
    • نبذة مختصرة :
      A preconditioning theory is presented which establishes sufficient conditions for multiplicative and additive Schwarz algorithms to yield self-adjoint positive definite preconditioners. It allows for the analysis and use of nonvariational and nonconvergent linear methods as preconditioners for conjugate gradient methods, and it is applied to domain decomposition and multigrid. It is illustrated why symmetrizing may be a bad idea for linear methods. It is conjectured that enforcing minimal symmetry achieves the best results when combined with conjugate gradient acceleration. Also, it is shown that the absence of symmetry in the linear preconditioner is advantageous when the linear method is accelerated by using the Bi-CGstab method. Numerical examples are presented for two test problems which illustrate the theory and conjectures.
    • الموضوع:
      Caltech Library Services; Article; PeerReviewed
    • Note:
      application/pdf
      Schwarz Methods: To Symmetrize or Not to Symmetrize
      English
    • Other Numbers:
      CIT oai:authors.library.caltech.edu:12608
      https://authors.library.caltech.edu/12608/1/HOLsiamjna97.pdf
      Holst, Michael and Vandewalle, Stefan (1997) Schwarz Methods: To Symmetrize or Not to Symmetrize. SIAM Journal on Numerical Analysis, 34 (2). pp. 699-722. ISSN 0036-1429. doi:10.1137/S0036142994275743. https://resolver.caltech.edu/CaltechAUTHORS:HOLsiamjna97
      1287034222
    • Contributing Source:
      CALIFORNIA INST OF TECH
      From OAIster®, provided by the OCLC Cooperative.
    • الرقم المعرف:
      edsoai.on1287034222
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