In this paper we consider the arithmetic mean method for solving large sparse systems of linear equations. This iterative method converges for systems with coefficient matrices that are symmetric positive definite or positive real or irreducible L-matrices with a strong diagonal dominance. The method is very suitable for parallel implementation on a multiprocessor system, such as the CRAY X-MP. Some numerical experiments on systems resulting from the discretization, by means of the usual 5-point difference formulae, of an elliptic partial differential equation are presented
Introduction One of the fundamental task of numerical computing is the ability to solve linear syst...
The most effective algorithms of solving large sparse linear system are Block Wiedemann and Block La...
AbstractAn algorithm is presented for the general solution of a set of linear equations Ax=b. The me...
In this paper we consider the arithmetic mean method for solving large sparse systems of linear equa...
AbstractIn this paper we consider thearithmetic mean method for solving large sparse systems of line...
In this paper we consider thearithmetic mean method for solving large sparse systems of linear equat...
In several recent works, the Arithmetic Mean Method for solving large sparse linear systems has been...
In this paper, we consider a new form of the arithmetic mean method for solving large block tridiago...
AbstractA class of parallel decomposition-type accelerated over-relaxation methods, including four a...
AbstractIn this paper, we consider a new form of the arithmetic mean method for solving large block ...
In this paper, we consider a new form of the arithmetic mean method for solving large block tridiago...
In the second edition of this classic monograph, complete with four new chapters and updated referen...
Many problems in applied mathematics can be formulated as a Sylvester matrix equation AX+XB=C. Itera...
We propose a novel iterative algorithm for solving a large sparse linear system. The method is based...
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate...
Introduction One of the fundamental task of numerical computing is the ability to solve linear syst...
The most effective algorithms of solving large sparse linear system are Block Wiedemann and Block La...
AbstractAn algorithm is presented for the general solution of a set of linear equations Ax=b. The me...
In this paper we consider the arithmetic mean method for solving large sparse systems of linear equa...
AbstractIn this paper we consider thearithmetic mean method for solving large sparse systems of line...
In this paper we consider thearithmetic mean method for solving large sparse systems of linear equat...
In several recent works, the Arithmetic Mean Method for solving large sparse linear systems has been...
In this paper, we consider a new form of the arithmetic mean method for solving large block tridiago...
AbstractA class of parallel decomposition-type accelerated over-relaxation methods, including four a...
AbstractIn this paper, we consider a new form of the arithmetic mean method for solving large block ...
In this paper, we consider a new form of the arithmetic mean method for solving large block tridiago...
In the second edition of this classic monograph, complete with four new chapters and updated referen...
Many problems in applied mathematics can be formulated as a Sylvester matrix equation AX+XB=C. Itera...
We propose a novel iterative algorithm for solving a large sparse linear system. The method is based...
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate...
Introduction One of the fundamental task of numerical computing is the ability to solve linear syst...
The most effective algorithms of solving large sparse linear system are Block Wiedemann and Block La...
AbstractAn algorithm is presented for the general solution of a set of linear equations Ax=b. The me...