In recent years, there has been considerable progress concerning preconditioned iterative methods for large and sparse systems of equations arising from the discretization of differential equations. Such methods are particularly attractive in the context of high-performance (parallel) computers. However, the implementation of a preconditioner is a nontrivial task. The focus of the present contribution is on a set of object-oriented software tools that support the construction of a family of preconditioners based on fast transforms. By combining objects of different classes, it is possible to conveniently construct any preconditioner within this family
This article surveys preconditioning techniques for the iterative solution of large linear systems, ...
The efficient parallel solution to large sparse linear systems of equations Ax = b is a central issu...
AbstractWe design, analyse and test a class of incomplete orthogonal factorization preconditioners c...
AbstractThe main difficulty in the implementation of most standard implicit Runge–Kutta (IRK) method...
We review current methods for preconditioning systems of equations for their solution using iterativ...
The main difficulty in the implementation of most standard implicit Runge-Kutta (IRK) methods applie...
The authors discuss the design of hypre, an object-oriented library for the solution of extremely la...
A popular class of preconditioners is known as incomplete factorizations. They can be thought of as ...
The computational solution of problems can be restricted by the availability of solution methods for...
The rapid improvement in computational power available due to faster chips and parallel processing i...
In this thesis, the design of the preconditioners we propose starts from applications instead of tre...
Iterative methods are currently the solvers of choice for large sparse linear systems of equations. ...
The rapid improvement ' in computational power available due to faster chips and parallel processing...
This paper describes and tests a parallel implementation of a factorized approximate inverse precond...
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate...
This article surveys preconditioning techniques for the iterative solution of large linear systems, ...
The efficient parallel solution to large sparse linear systems of equations Ax = b is a central issu...
AbstractWe design, analyse and test a class of incomplete orthogonal factorization preconditioners c...
AbstractThe main difficulty in the implementation of most standard implicit Runge–Kutta (IRK) method...
We review current methods for preconditioning systems of equations for their solution using iterativ...
The main difficulty in the implementation of most standard implicit Runge-Kutta (IRK) methods applie...
The authors discuss the design of hypre, an object-oriented library for the solution of extremely la...
A popular class of preconditioners is known as incomplete factorizations. They can be thought of as ...
The computational solution of problems can be restricted by the availability of solution methods for...
The rapid improvement in computational power available due to faster chips and parallel processing i...
In this thesis, the design of the preconditioners we propose starts from applications instead of tre...
Iterative methods are currently the solvers of choice for large sparse linear systems of equations. ...
The rapid improvement ' in computational power available due to faster chips and parallel processing...
This paper describes and tests a parallel implementation of a factorized approximate inverse precond...
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate...
This article surveys preconditioning techniques for the iterative solution of large linear systems, ...
The efficient parallel solution to large sparse linear systems of equations Ax = b is a central issu...
AbstractWe design, analyse and test a class of incomplete orthogonal factorization preconditioners c...