In this paper, we consider a new form of the arithmetic mean method for solving large block tridiagonal linear systems. The 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. When the coefficient matrix is symmetric positive definite, an additive preconditioner for the conjugate gradient method is derived.Both the iterative method and the preconditioner are very suitable for parallel implementation on a multivector computer. Some numerical experiments on systems resulting from the discretization of an elliptic partial differential equation are carried out on the CRAY-MP
A parallel variant of the block Gauss-Seidel iteration is presented for the solution of Mock tridiag...
The block preconditioned conjugate gradient (BPCG) methods, even if very effective for solving the l...
In this paper we consider the arithmetic mean method for solving large sparse systems of linear equa...
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 this paper, we consider a new form of the arithmetic mean method for solving large block tridiago...
In this report we consider a new version of the arithmetic mean method for solving large block tridi...
In this report we consider two parallel additive preconditioners for solving block tridiagonal linea...
This paper is concerned with the solution of block tridiagonal linear algebraic systems by two diffe...
This paper is concerned with the solution of block tridiagonal linear systems by the preconditioned ...
AbstractThe explicit structure of the inverse of block tridiagonal matrices is presented in terms of...
AbstractFor large-scale system of linear equations with symmetric positive definite block coefficien...
We study the conditioning and the parallel solution of banded linear systems of algebraic equations....
AbstractWe study the conditioning and the parallel solution of banded linear systems of algebraic eq...
The block preconditioned conjugate gradient (BPCG) methods, even if very effective for solving the l...
A parallel variant of the block Gauss-Seidel iteration is presented for the solution of Mock tridiag...
The block preconditioned conjugate gradient (BPCG) methods, even if very effective for solving the l...
In this paper we consider the arithmetic mean method for solving large sparse systems of linear equa...
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 this paper, we consider a new form of the arithmetic mean method for solving large block tridiago...
In this report we consider a new version of the arithmetic mean method for solving large block tridi...
In this report we consider two parallel additive preconditioners for solving block tridiagonal linea...
This paper is concerned with the solution of block tridiagonal linear algebraic systems by two diffe...
This paper is concerned with the solution of block tridiagonal linear systems by the preconditioned ...
AbstractThe explicit structure of the inverse of block tridiagonal matrices is presented in terms of...
AbstractFor large-scale system of linear equations with symmetric positive definite block coefficien...
We study the conditioning and the parallel solution of banded linear systems of algebraic equations....
AbstractWe study the conditioning and the parallel solution of banded linear systems of algebraic eq...
The block preconditioned conjugate gradient (BPCG) methods, even if very effective for solving the l...
A parallel variant of the block Gauss-Seidel iteration is presented for the solution of Mock tridiag...
The block preconditioned conjugate gradient (BPCG) methods, even if very effective for solving the l...
In this paper we consider the arithmetic mean method for solving large sparse systems of linear equa...