Lanczos-type variants of the COCR method for complex nonsymmetric linear systems

Motivated by the celebrated extending applications of the well-established complex Biconjugate Gradient (CBiCG) method to deal with large three-dimensional electromagnetic scattering problems by Pocock and Walker [M.D. Pocock, S.P. Walker, The complex Bi-conjugate Gradient solver applied to large electromagnetic scattering problems, computational costs, and cost scalings, IEEE Trans. Antennas Propagat. 45 (1997) 140-146], three Lanczos-type variants of the recent Conjugate A-Orthogonal Conjugate Residual (COCR) method of Sogabe and Zhang [T. Sogabe, S.-L. Zhang, A COCR method for solving complex symmetric linear systems, J. Comput. Appl. Math. 199 (2007) 297-303] are explored for the solution of complex nonsymmetric linear systems. The first two can be respectively considered as mathematically equivalent but numerically improved popularizing versions of the BiCR and CRS methods for complex systems presented in Sogabe's Ph.D. Dissertation. And the last one is somewhat new and is a stabilized and more smoothly converging variant of the first two in some circumstances. The presented algorithms are with the hope of obtaining smoother and, hopefully, faster convergence behavior in comparison with the CBiCG method as well as its two corresponding variants. This motivation is demonstrated by numerical experiments performed on some selective matrices borrowed from The University of Florida Sparse Matrix Collection by Davis.

[1]  M. Benzi Preconditioning techniques for large linear systems: a survey , 2002 .

[2]  Zhishun A. Liu,et al.  A Look Ahead Lanczos Algorithm for Unsymmetric Matrices , 1985 .

[3]  C. Brezinski,et al.  Hybrid procedures for solving linear systems , 1994 .

[4]  D. R. Fokkema,et al.  BiCGstab(ell) for Linear Equations involving Unsymmetric Matrices with Complex Spectrum , 1993 .

[5]  Martin H. Gutknecht,et al.  Variants of BICGSTAB for Matrices with Complex Spectrum , 1993, SIAM J. Sci. Comput..

[6]  C. Lanczos Solution of Systems of Linear Equations by Minimized Iterations1 , 1952 .

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

[8]  Richard Barrett,et al.  Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods , 1994, Other Titles in Applied Mathematics.

[9]  M. Gutknecht,et al.  Residual Smoothing Techniques: Do They Improve the Limiting Accuracy of Iterative Solvers? , 1999 .

[10]  Bruce Hendrickson,et al.  An Improved Spectral Graph Partitioning Algorithm for Mapping Parallel Computations , 1995, SIAM J. Sci. Comput..

[11]  T. Sogabe,et al.  A COCR method for solving complex symmetric linear systems , 2007 .

[12]  E. Stiefel,et al.  Relaxationsmethoden bester Strategie zur Lösung linearer Gleichungssysteme , 1955 .

[13]  Thomas Weiland,et al.  Comparison of Krylov-type methods for complex linear systems applied to high-voltage problems , 1998 .

[14]  Miroslav Rozlozník,et al.  By How Much Can Residual Minimization Accelerate the Convergence of Orthogonal Residual Methods? , 2001, Numerical Algorithms.

[15]  Beresford N. Parlett,et al.  Reduction to Tridiagonal Form and Minimal Realizations , 1992, SIAM J. Matrix Anal. Appl..

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

[17]  Gérard Meurant,et al.  Complex conjugate gradient methods , 1993, Numerical Algorithms.

[18]  Roland W. Freund,et al.  An Implementation of the Look-Ahead Lanczos Algorithm for Non-Hermitian Matrices , 1993, SIAM J. Sci. Comput..

[19]  J. Cullum,et al.  Lanczos algorithms for large symmetric eigenvalue computations , 1985 .

[20]  M. D. Pocock,et al.  The complex bi-conjugate gradient solver applied to large electromagnetic scattering problems, computational costs, and cost scalings , 1997 .

[21]  C. Lanczos An iteration method for the solution of the eigenvalue problem of linear differential and integral operators , 1950 .

[22]  Martin H. Gutknecht,et al.  Lanczos-type solvers for nonsymmetric linear systems of equations , 1997, Acta Numerica.

[23]  R. Weiss A theoretical overview of Krylov subspace methods , 1995 .

[24]  知広 曽我部 Extensions of the conjugate residual method , 2006 .

[25]  Anne Greenbaum,et al.  Relations between Galerkin and Norm-Minimizing Iterative Methods for Solving Linear Systems , 1996, SIAM J. Matrix Anal. Appl..

[26]  J. Cullum,et al.  A generalized nonsymmetric Lanczos procedure , 1989 .

[27]  Rüdiger Weiss,et al.  Parameter-Free Iterative Linear Solvers , 1996 .

[28]  Markus Clemens,et al.  Iterative Methods for the Solution of Very Large Complex Symmetric Linear Systems of Equations in El , 1996 .

[29]  D. Day,et al.  An Efficient Implementation of the Nonsymmetric Lanczos Algorithm , 1997 .

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

[31]  Jane K. Collum Peaks, plateaus, numerical instabilities in a Galerkin minimal residual pair of methods for solving Ax = b , 1995 .

[32]  Roland W. Freund,et al.  A Transpose-Free Quasi-Minimal Residual Algorithm for Non-Hermitian Linear Systems , 1993, SIAM J. Sci. Comput..

[33]  Y. Saad,et al.  Iterative solution of linear systems in the 20th century , 2000 .

[34]  Homer F. Walker,et al.  Residual smoothing and peak/plateau behavior in Krylov subspace methods , 1995 .

[35]  Raj Mittra,et al.  The biconjugate gradient method for electromagnetic scattering , 1990 .

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

[37]  David Pardo,et al.  Electromagnetic Scattering Problems , 2007 .

[38]  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..

[39]  Jack J. Dongarra,et al.  Guest Editors Introduction to the top 10 algorithms , 2000, Comput. Sci. Eng..

[40]  Rüdiger Weiss,et al.  Properties of generalized conjugate gradient methods , 1994, Numer. Linear Algebra Appl..

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

[42]  M. Sugihara,et al.  An extension of the conjugate residual method to nonsymmetric linear systems , 2009 .

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

[44]  G. Markham Conjugate Gradient Type Methods for Indefinite, Asymmetric, and Complex Systems , 1990 .

[45]  H. V. D. Vorst,et al.  A Petrov-Galerkin type method for solving Axk=b, where A is symmetric complex , 1990 .

[46]  Homer F. Walker,et al.  Residual Smoothing Techniques for Iterative Methods , 1994, SIAM J. Sci. Comput..

[47]  Peter N. Brown,et al.  A Theoretical Comparison of the Arnoldi and GMRES Algorithms , 1991, SIAM J. Sci. Comput..

[48]  H. V. D. Vorst,et al.  The convergence behaviour of preconditioned CG and CG-S in the presence of rounding errors , 1991 .

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

[50]  D. A. H. Jacobs,et al.  A Generalization of the Conjugate-Gradient Method to Solve Complex Systems , 1986 .

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

[52]  C. Brezinski Padé-type approximation and general orthogonal polynomials , 1980 .

[53]  T. Sarkar On the Application of the Generalized BiConjugate Gradient Method , 1987 .

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

[55]  Miroslav Rozlozník,et al.  A framework for generalized conjugate gradient methods-with special emphasis on contributions by Rüdiger Weiss , 2002 .

[56]  Yong Zhang,et al.  Application of the incomplete Cholesky factorization preconditioned Krylov subspace method to the vector finite element method for 3-D electromagnetic scattering problems , 2010, Comput. Phys. Commun..

[57]  Rüdiger Weiss,et al.  Convergence behavior of generalized conjugate gradient methods , 1990 .

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

[59]  H. V. D. Vorst,et al.  An overview of approaches for the stable computation of hybrid BiCG methods , 1995 .

[60]  Hassane Sadok,et al.  Analysis of the convergence of the minimal and the orthogonal residual methods , 2005, Numerical Algorithms.