AbstractAn approach to preconditioning linear systems is presented, which is well suitable for parallel implementation. Such approach leads to efficient parallel linear systems solvers, as well as to new schemes for matrix inversion, in some special cases
This book is primarily intended as a research monograph that could also be used in graduate courses ...
In this paper, we present techniques for inverting sparse, symmetric and positive definite matrices ...
AbstractThe complexity of performing matrix computations, such as solving a linear system, inverting...
AbstractAn approach to preconditioning linear systems is presented, which is well suitable for paral...
AbstractWe review some of the most important resulsts in the area of fast parallel algorithms for th...
We review some of the most important results in the area of fast parallel algorithms for the solutio...
AbstractWe estimate parallel complexity of several matrix computations under both Boolean and arithm...
The AISM (Approximate Inverse based on the Sherman--Morrison Formula) method is one of the existing ...
The Sherman--Morrison formula is one scheme for computing the approximate inverse preconditioner of ...
The thesis is concerned with the inversion of matrices and the solution of linear systems and eigens...
AbstractA new parallel algorithm for the solution of linear systems, based upon the Monte Carlo appr...
The class of preconditioning that approximates the inverse of the matrix A is studied in the thesis....
AbstractThe known algorithms invert an n × n Toeplitz matrix in sequential arithmetic time O(n log2 ...
In this review paper, we consider some important developments and trends in algorithm design for t...
We review current methods for preconditioning systems of equations for their solution using iterativ...
This book is primarily intended as a research monograph that could also be used in graduate courses ...
In this paper, we present techniques for inverting sparse, symmetric and positive definite matrices ...
AbstractThe complexity of performing matrix computations, such as solving a linear system, inverting...
AbstractAn approach to preconditioning linear systems is presented, which is well suitable for paral...
AbstractWe review some of the most important resulsts in the area of fast parallel algorithms for th...
We review some of the most important results in the area of fast parallel algorithms for the solutio...
AbstractWe estimate parallel complexity of several matrix computations under both Boolean and arithm...
The AISM (Approximate Inverse based on the Sherman--Morrison Formula) method is one of the existing ...
The Sherman--Morrison formula is one scheme for computing the approximate inverse preconditioner of ...
The thesis is concerned with the inversion of matrices and the solution of linear systems and eigens...
AbstractA new parallel algorithm for the solution of linear systems, based upon the Monte Carlo appr...
The class of preconditioning that approximates the inverse of the matrix A is studied in the thesis....
AbstractThe known algorithms invert an n × n Toeplitz matrix in sequential arithmetic time O(n log2 ...
In this review paper, we consider some important developments and trends in algorithm design for t...
We review current methods for preconditioning systems of equations for their solution using iterativ...
This book is primarily intended as a research monograph that could also be used in graduate courses ...
In this paper, we present techniques for inverting sparse, symmetric and positive definite matrices ...
AbstractThe complexity of performing matrix computations, such as solving a linear system, inverting...
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