Modified block preconditioner for generalized saddle point matrices with highly singular(1,1) blocks

ABSTRACT

In this paper, based on the preconditioners presented by Zhang [A new preconditioner for generalized saddle matrices with highly singular(1,1) blocks. Int J Comput Maths. 2014;91(9):2091-2101], we consider a modified block preconditioner for generalized saddle point matrices whose coefficient matrices have singular (1,1) blocks. Moreover, theoretical analysis gives the eigenvalue distribution, forms of the eigenvectors and the minimal polynomial. Finally, numerical examples show the eigenvalue distribution with the presented preconditioner and confirm our analysis.     

A note on spectrum distribution of constraint preconditioned generalized saddle point matrices

In this note, results concerning the eigenvalue distribution and form of the eigenvectors of the constraint preconditioned generalized saddle point matrix and its minimal polynomial are given. These results extend previous ones that appeared in the literature. Copyright © 2009 John Wiley & Sons, Ltd.     

Eigenvalue estimates for preconditioned saddle point matrices

New accurate eigenvalue bounds for symmetric matrices of saddle point form are derived and applied for both unpreconditioned and preconditioned versions of the matrices. The estimates enable a better understanding of how preconditioners should be chosen. The preconditioners provide efficient iterative solution of the corresponding linear systems with, for some important applications, an optimal order of computational complexity. The methods are applied for Stokes problem and for linear elasticity problems. Copyright © 2005 John Wiley & Sons, Ltd.     

On constraint preconditioners for generalized saddle point matrices

For the iterative solution of large sparse generalized saddle point problems, a class of new constraint preconditioners is presented, and the spectral properties and parameter choices are discussed. Numerical experiments are used to demonstrate the feasibility and effectiveness of the new preconditioners, as well as their advantages over the modified product-type skew-Hermitian triangular splitting (MPSTS) preconditioners.     

A comparison of overlapping Schwarz methods and block preconditioners for saddle point problems

Three domain decomposition methods for saddle point problems are introduced and compared. The first two are block‐diagonal and block‐triangular preconditioners with diagonal blocks approximated by an overlapping Schwarz technique with positive definite local and coarse problems. The third is an overlapping Schwarz preconditioner based on indefinite local and coarse problems. Numerical experiments show that while all three methods are numerically scalable, the last method is almost always the most efficient. Copyright © 2000 John Wiley & Sons, Ltd.     

Spectral properties of primal-based penalty preconditioners for saddle point problems

For large and sparse saddle point linear systems, this paper gives further spectral properties of the primal-based penalty preconditioners introduced in [C.R. Dohrmann, R.B. Lehoucq, A primal-based penalty preconditioner for elliptic saddle point systems, SIAM J. Numer. Anal. 44 (2006) 270-282]. The regions containing the real and non-real eigenvalues of the preconditioned matrix are obtained. The model of the Stokes problem is supplemented to illustrate the theoretical results and to test the quality of the primal-based penalty preconditioner.     

A class of constraint preconditioners for nonsymmetric saddle point matrices

We consider the use of a class of constraint preconditioners for the application of the Krylov subspace iterative method to the solution of large nonsymmetric, indefinite linear systems. The eigensolution distribution of the preconditioned matrix is determined and the convergence behavior of a Krylov subspace method such as GMRES is described. The choices of the parameter matrices and the implementation of the preconditioning step are discussed. Numerical experiments are presented. This work is supported by NSFC Projects 10171021 and 10471027.     

A note for preconditioning nonsymmetric matrices

In this paper, we consider preconditioners for generalized saddle point systems with a nonsymmetric coefficient matrix. A constraint preconditioner for this systems is constructed, and some spectral properties of the preconditioned matrix are given. Our results extend the corresponding ones in [3] and [4].     

A splitting preconditioner for saddle point problems

For large sparse systems of linear equations iterative techniques are attractive. In this paper, we study a splitting method for an important class of symmetric and indefinite system. Theoretical analyses show that this method converges to the unique solution of the system of linear equations for all t>0 (t is the parameter). Moreover, all the eigenvalues of the iteration matrix are real and nonnegative and the spectral radius of the iteration matrix is decreasing with respect to the parameter t. Besides, a preconditioning strategy based on the splitting of the symmetric and indefinite coefficient matrices is proposed. The eigensolution of the preconditioned matrix is described and an upper bound of the degree of the minimal polynomials for the preconditioned matrix is obtained. Numerical experiments of a model Stokes problem and a least‐squares problem with linear constraints presented to illustrate the effectiveness of the method. Copyright © 2011 John Wiley & Sons, Ltd.     

A numerical comparison of two minimal residual methods for linear polynomials in unitary matrices

Two minimal residual methods for solving linear systems of the form (αU + βI)x = b, where U is a unitary matrix, are compared numerically. The first method uses conventional Krylov subspaces, while the second involves generalized Krylov subspaces. Experiments favor the second method if |α| > |β|. Moreover, the greater the ratio |α|/|β|, the higher the superiority of the second method.     

On block preconditioners for saddle point problems with singular or indefinite (1, 1) block

We discuss a class of preconditioning methods for the iterative solution of symmetric algebraic saddle point problems, where the (1, 1) block matrix may be indefinite or singular. Such problems may arise, e.g. from discrete approximations of certain partial differential equations, such as the Maxwell time harmonic equations. We prove that, under mild assumptions on the underlying problem, a class of block preconditioners (including block diagonal, triangular and symmetric indefinite preconditioners) can be chosen in a way which guarantees that the convergence rate of the preconditioned conjugate residuals method is independent of the discretization mesh parameter. We provide examples of such preconditioners that do not require additional scaling. Copyright © 2010 John Wiley & Sons, Ltd.     

On computing of block ILU preconditioner for block tridiagonal systems

We present the recurrence formulas for computing the approximate inverse factors of tridiagonal and pentadiagonal matrices using bordering technique. Resulting algorithms are used to approximate the inverse of pivot blocks needed for constructing block ILU preconditioners for solving the block tridiagonal linear systems, arising from discretization of partial differential equations. Resulting preconditioners are suitable for parallel implementation. Comparison with other methods are also included.     

A note on constraint preconditioners for nonsymmetric saddle point problems

A class of constraint preconditioners for solving two‐by‐two block linear equations with the (1,2)‐block being the transpose of the (2,1)‐block and the (2,2)‐block being zero was investigated in a recent paper of Cao (Numer. Math. 2006; 103 :47–61). In this short note, we extend his idea by allowing the (1,2)‐block to be not equal to the transpose of the (2,1)‐block. Results concerning the spectrum, the form of the eigenvectors and the convergence behaviour of a Krylov subspace method, such as GMRES are presented. Copyright © 2007 John Wiley & Sons, Ltd.     

Comment on ‘Preconditioning of matrices partitioned in 2 Œ 2 block form: Eigenvalue estimates and Schwarz DD for mixed FEM’ by Owe Axelsson,Radim Blaheta

In this note, we discuss the inverse representations of regularized saddle point matrices and point out that some conclusions given by Axelsson and Blaheta in [Numerical Linear Algebra with Applications, 2010,17:787–810 ] are not true.Copyright © 2011 John Wiley & Sons, Ltd.     

A parameterized extended shift-splitting preconditioner for nonsymmetric saddle point problems

In this article, a parameterized extended shift-splitting (PESS) method and its induced preconditioner are given for solving nonsingular and nonsymmetric saddle point problems with nonsymmetric positive definite (1,1) part. The convergence analysis of the $PESS$ iteration method is discussed. The distribution of eigenvalues of the preconditioned matrix is provided. A number of experiments are given to verify the efficiency of the $PESS$ method for solving nonsymmetric saddle-point problems.     

On parameterized block triangular preconditioners for generalized saddle point problems

In this paper, we discuss two classes of parameterized block triangular preconditioners for the generalized saddle point problems. These preconditioners generalize the common block diagonal and triangular preconditioners. We will give distributions of the eigenvalues of the preconditioned matrix and provide estimates for the interval containing the real eigenvalues. Numerical experiments of a model Stokes problem are presented.     

A note on eigenvalue distribution of constraint‐preconditioned symmetric saddle point matrices

In this note, some inaccuracies in the article (Numer. Linear Algebra Appl. 2012; 19:754–772) are pointed out and correct results are presented. Copyright © 2013 John Wiley & Sons, Ltd.     

Uzawa type algorithms for nonsymmetric saddle point problems

In this paper, we consider iterative algorithms of Uzawa type for solving linear nonsymmetric saddle point problems. Specifically, we consider systems, written as usual in block form, where the upper left block is an invertible linear operator with positive definite symmetric part. Such saddle point problems arise, for example, in certain finite element and finite difference discretizations of Navier-Stokes equations, Oseen equations, and mixed finite element discretization of second order convection-diffusion problems. We consider two algorithms, each of which utilizes a preconditioner for the operator in the upper left block. Convergence results for the algorithms are established in appropriate norms. The convergence of one of the algorithms is shown assuming only that the preconditioner is spectrally equivalent to the inverse of the symmetric part of the operator. The other algorithm is shown to converge provided that the preconditioner is a sufficiently accurate approximation of the inverse of the upper left block. Applications to the solution of steady-state Navier-Stokes equations are discussed, and, finally, the results of numerical experiments involving the algorithms are presented.

     

Analysis of iterative methods for saddle point problems: a unified approach

In this paper two classes of iterative methods for saddle point problems are considered: inexact Uzawa algorithms and a class of methods with symmetric preconditioners. In both cases the iteration matrix can be transformed to a symmetric matrix by block diagonal matrices, a simple but essential observation which allows one to estimate the convergence rate of both classes by studying associated eigenvalue problems. The obtained estimates apply for a wider range of situations and are partially sharper than the known estimates in literature. A few numerical tests are given which confirm the sharpness of the estimates.