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NEW CONVERGENCE ANALYSIS OF GMRES WITH WEIGHTED NORMS, PRECONDITIONING, AND DEFLATION, LEADING TO A NEW DEFLATION SPACE

  • Temple University

Research output: Contribution to journalArticlepeer-review

Abstract

New convergence bounds are presented for weighted, preconditioned, and deflated GMRES for the solution of large, sparse, non-Hermitian linear systems. These bounds are given for the case when the Hermitian part of the coefficient matrix is positive definite, the preconditioner is Hermitian positive definite, and the weight is equal to the preconditioner. The new bounds are a novel contribution in and of themselves. In addition, they are sufficiently explicit to indicate how to choose the preconditioner and the deflation space to accelerate the convergence. One such choice of deflating space is presented, and numerical experiments illustrate the effectiveness of such space.

Original languageEnglish
Pages (from-to)1721-1745
Number of pages25
JournalSIAM Journal on Matrix Analysis and Applications
Volume45
Issue number4
DOIs
Publication statusPublished - 1 Jan 2024

Keywords

  • convergence analysis
  • deflation
  • deflation space
  • domain decomposition
  • linear solver
  • preconditioning

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