On choice of preconditioner for minimum residual methods for nonsymmetric matrices

Existing convergence bounds for Krylov subspace methods such as GMRES for nonsymmetric linear systems give little mathematical guidance for the choice of preconditioner. Here, we establish a desirable mathematical property of a preconditioner which guarantees that convergence of a minimum residual method will essentially depend only on the eigenvalues of the preconditioned system, as is true in the symmetric case. Our theory covers only a subset of nonsymmetric coefficient matrices but computations indicate that it might be more generally applicable.

[1]  Y. Saad,et al.  GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems , 1986 .

[2]  S. Eisenstat,et al.  Variational Iterative Methods for Nonsymmetric Systems of Linear Equations , 1983 .

[3]  Barry Lee,et al.  Finite elements and fast iterative solvers: with applications in incompressible fluid dynamics , 2006, Math. Comput..

[4]  D. R. Fokkema,et al.  BICGSTAB( L ) FOR LINEAR EQUATIONS INVOLVING UNSYMMETRIC MATRICES WITH COMPLEX , 1993 .

[5]  Anne Greenbaum,et al.  Iterative methods for solving linear systems , 1997, Frontiers in applied mathematics.

[6]  P. Sonneveld CGS, A Fast Lanczos-Type Solver for Nonsymmetric Linear systems , 1989 .

[7]  Lloyd N. Trefethen,et al.  How Fast are Nonsymmetric Matrix Iterations? , 1992, SIAM J. Matrix Anal. Appl..

[8]  W. Joubert,et al.  Necessary and sufficient conditions for the simplification of generalized conjugate-gradient algorithms , 1987 .

[9]  Olga Taussky,et al.  The role of symmetric matrices in the study of general matrices , 1972 .

[10]  Howard C. Elman,et al.  Algorithm 866: IFISS, a Matlab toolbox for modelling incompressible flow , 2007, TOMS.

[11]  Robert H. Halstead,et al.  Matrix Computations , 2011, Encyclopedia of Parallel Computing.

[12]  Henk A. van der Vorst,et al.  Bi-CGSTAB: A Fast and Smoothly Converging Variant of Bi-CG for the Solution of Nonsymmetric Linear Systems , 1992, SIAM J. Sci. Comput..

[13]  Michele Benzi,et al.  On the eigenvalues of a class of saddle point matrices , 2006, Numerische Mathematik.

[14]  Zdenek Strakos,et al.  On Optimal Short Recurrences for Generating Orthogonal Krylov Subspace Bases , 2008, SIAM Rev..

[15]  Azeddine Essai Weighted FOM and GMRES for solving nonsymmetric linear systems , 2004, Numerical Algorithms.

[16]  Beresford N. Parlett,et al.  On nonsymmetric saddle point matrices that allow conjugate gradient iterations , 2008, Numerische Mathematik.

[17]  Timothy A. Davis,et al.  The university of Florida sparse matrix collection , 2011, TOMS.

[18]  M. Hestenes,et al.  Methods of conjugate gradients for solving linear systems , 1952 .

[19]  M. Arioli,et al.  Krylov sequences of maximal length and convergence of GMRES , 1997 .

[20]  R. Fletcher Conjugate gradient methods for indefinite systems , 1976 .

[21]  Zhongxiao Jia,et al.  A power sparse approximate inverse preconditioning procedure for large sparse linear systems , 2009, Numer. Linear Algebra Appl..

[22]  A. Ramage A multigrid preconditioner for stabilised discretisations of advection-diffusion problems , 1999 .

[23]  J. Meijerink,et al.  An iterative solution method for linear systems of which the coefficient matrix is a symmetric -matrix , 1977 .

[24]  John G. Lewis,et al.  Sparse matrix test problems , 1982, SGNM.

[25]  David L. Darmofal,et al.  The Importance of Eigenvectors for Local Preconditioners of the Euler Equations , 1996 .

[26]  T. Manteuffel,et al.  A taxonomy for conjugate gradient methods , 1990 .

[27]  Martin Stoll,et al.  Combination Preconditioning and the Bramble-Pasciak+ Preconditioner , 2008, SIAM J. Matrix Anal. Appl..

[28]  Lothar Reichel,et al.  A fast minimal residual algorithm for shifted unitary matrices , 1994, Numer. Linear Algebra Appl..

[29]  T. Manteuffel,et al.  Necessary and Sufficient Conditions for the Existence of a Conjugate Gradient Method , 1984 .

[30]  R. Freund,et al.  QMR: a quasi-minimal residual method for non-Hermitian linear systems , 1991 .

[31]  Valeria Simoncini,et al.  The effect of non-optimal bases on the convergence of Krylov subspace methods , 2005, Numerische Mathematik.

[32]  P. Lancaster,et al.  Indefinite Linear Algebra and Applications , 2005 .

[33]  Anne Greenbaum,et al.  Any Nonincreasing Convergence Curve is Possible for GMRES , 1996, SIAM J. Matrix Anal. Appl..

[34]  H. V. der Residual Replacement Strategies for Krylov Subspace Iterative Methods for the Convergence of True Residuals , 2000 .

[35]  Zdenek Strakos,et al.  GMRES Convergence Analysis for a Convection-Diffusion Model Problem , 2005, SIAM J. Sci. Comput..

[36]  Howard C. Elman,et al.  Finite Elements and Fast Iterative Solvers: with Applications in Incompressible Fluid Dynamics , 2014 .

[37]  Valeria Simoncini,et al.  Recent computational developments in Krylov subspace methods for linear systems , 2007, Numer. Linear Algebra Appl..

[38]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[39]  I. Duff,et al.  Direct Methods for Sparse Matrices , 1987 .

[40]  Yousef Saad,et al.  High-order ILU preconditioners for CFD problems , 2000 .

[41]  M. Saunders,et al.  Solution of Sparse Indefinite Systems of Linear Equations , 1975 .

[42]  Ting-Zhu Huang,et al.  On some new approximate factorization methods for block tridiagonal matrices suitable for vector and parallel processors , 2009, Math. Comput. Simul..

[43]  Louis A. Hageman,et al.  Iterative Solution of Large Linear Systems. , 1971 .

[44]  M. Benzi,et al.  A comparative study of sparse approximate inverse preconditioners , 1999 .

[45]  M. Eiermann,et al.  Geometric aspects of the theory of Krylov subspace methods , 2001, Acta Numerica.

[46]  Michael Eiermann,et al.  Fields of values and iterative methods , 1993 .

[47]  Eugene E. Tyrtyshnikov,et al.  Some Remarks on the Elman Estimate for GMRES , 2005, SIAM J. Matrix Anal. Appl..

[48]  Yousef Saad,et al.  Iterative methods for sparse linear systems , 2003 .

[49]  L. Trefethen,et al.  Spectra and pseudospectra : the behavior of nonnormal matrices and operators , 2005 .

[50]  Paul E. Saylor,et al.  The Role of the Inner Product in Stopping Criteria for Conjugate Gradient Iterations , 2001 .

[51]  Timothy A. Davis,et al.  Direct methods for sparse linear systems , 2006, Fundamentals of algorithms.

[52]  G. Meurant,et al.  The Lanczos and conjugate gradient algorithms in finite precision arithmetic , 2006, Acta Numerica.

[53]  Jörg Liesen,et al.  The Faber-Manteuffel Theorem for Linear Operators , 2008, SIAM J. Numer. Anal..

[54]  Qiang Ye,et al.  Residual Replacement Strategies for Krylov Subspace Iterative Methods for the Convergence of True Residuals , 2000, SIAM J. Sci. Comput..

[55]  Hassane Sadok,et al.  A new look at CMRH and its relation to GMRES , 2012 .