AbstractThis paper will present a new method of adaptively constructing block iterative methods based on Local Sensitivity Analysis (LSA). The method can be used in the context of geometric and algebraic multigrid methods for constructing smoothers, and in the context of Krylov methods for constructing block preconditioners. It is suitable for both constant and variable coefficient problems. Furthermore, the method can be applied to systems arising from both scalar and coupled system partial differential equations (PDEs), as well as linear systems that do not arise from PDEs. The simplicity of the method will allow it to be easily incorporated into existing multigrid and Krylov solvers while providing a powerful tool for adaptively construc...
Abstract. Most efficient linear solvers use composable algorithmic components, with the most common ...
AbstractThe use of preconditioned Krylov methods is in many applications mandatory for computing eff...
AbstractThe approximate solutions in standard iteration methods for linear systems Ax=b, with A an n...
AbstractThis paper will present a new method of adaptively constructing block iterative methods base...
Solving linear systems arising from systems of partial differential equations, multigrid and multile...
International audienceThis paper introduces an adaptive preconditioner for iterative solution of spa...
This presentation is intended to review the state-of-the-art of iterative methods for solving large ...
This article has two main objectives: one is to describe some extensions of an adaptive Algebraic Mu...
Inexact (variable) preconditioning of Multilevel Krylov methods (MK methods) for the solution of lin...
This graduate-level text examines the practical use of iterative methods in solving large, sparse sy...
Many scientific applications require the solution of large and sparse linear systems of equations us...
When simulating a mechanism from science or engineering, or an industrial process, one is frequently...
In the last two decades, substantial effort has been devoted to solve large systems of linear equati...
AbstractWe present an efficient and effective preconditioning method for time-dependent simulations ...
Many scientific applications require the solution of large and sparse linear systems of equations us...
Abstract. Most efficient linear solvers use composable algorithmic components, with the most common ...
AbstractThe use of preconditioned Krylov methods is in many applications mandatory for computing eff...
AbstractThe approximate solutions in standard iteration methods for linear systems Ax=b, with A an n...
AbstractThis paper will present a new method of adaptively constructing block iterative methods base...
Solving linear systems arising from systems of partial differential equations, multigrid and multile...
International audienceThis paper introduces an adaptive preconditioner for iterative solution of spa...
This presentation is intended to review the state-of-the-art of iterative methods for solving large ...
This article has two main objectives: one is to describe some extensions of an adaptive Algebraic Mu...
Inexact (variable) preconditioning of Multilevel Krylov methods (MK methods) for the solution of lin...
This graduate-level text examines the practical use of iterative methods in solving large, sparse sy...
Many scientific applications require the solution of large and sparse linear systems of equations us...
When simulating a mechanism from science or engineering, or an industrial process, one is frequently...
In the last two decades, substantial effort has been devoted to solve large systems of linear equati...
AbstractWe present an efficient and effective preconditioning method for time-dependent simulations ...
Many scientific applications require the solution of large and sparse linear systems of equations us...
Abstract. Most efficient linear solvers use composable algorithmic components, with the most common ...
AbstractThe use of preconditioned Krylov methods is in many applications mandatory for computing eff...
AbstractThe approximate solutions in standard iteration methods for linear systems Ax=b, with A an n...