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...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...
We propose an efficient and robust algorithm to solve the steady Euler equations on unstructured gri...
Many scientific applications require the solution of large and sparse linear systems of equations us...
AbstractThis paper will present a new method of adaptively constructing block iterative methods base...
This graduate-level text examines the practical use of iterative methods in solving large, sparse sy...
Inexact (variable) preconditioning of Multilevel Krylov methods (MK methods) for the solution of lin...
This presentation is intended to review the state-of-the-art of iterative methods for solving large ...
After introduction of the model problem we derive its weak formulation, show the existence and the u...
Abstract: We introduce an adaptive algebraic multigrid method (AMG) for numerical solution...
We consider the solution of block-coupled large-scale linear systems of equations, arising from the ...
Solving linear systems arising from systems of partial differential equations, multigrid and multile...
The present work is concerned with topics related to some adaptive methods for the approximate solut...
A local multilevel product algorithm and its additive version are analyzed for linear systems arisin...
In 2006 the Multi-Preconditioned Conjugate Gradient (MPCG) algorithm was introduced by Bridson and G...
Block iterative methods are extremely important as smoothers for multigrid methods, as preconditione...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...
We propose an efficient and robust algorithm to solve the steady Euler equations on unstructured gri...
Many scientific applications require the solution of large and sparse linear systems of equations us...
AbstractThis paper will present a new method of adaptively constructing block iterative methods base...
This graduate-level text examines the practical use of iterative methods in solving large, sparse sy...
Inexact (variable) preconditioning of Multilevel Krylov methods (MK methods) for the solution of lin...
This presentation is intended to review the state-of-the-art of iterative methods for solving large ...
After introduction of the model problem we derive its weak formulation, show the existence and the u...
Abstract: We introduce an adaptive algebraic multigrid method (AMG) for numerical solution...
We consider the solution of block-coupled large-scale linear systems of equations, arising from the ...
Solving linear systems arising from systems of partial differential equations, multigrid and multile...
The present work is concerned with topics related to some adaptive methods for the approximate solut...
A local multilevel product algorithm and its additive version are analyzed for linear systems arisin...
In 2006 the Multi-Preconditioned Conjugate Gradient (MPCG) algorithm was introduced by Bridson and G...
Block iterative methods are extremely important as smoothers for multigrid methods, as preconditione...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...
We propose an efficient and robust algorithm to solve the steady Euler equations on unstructured gri...
Many scientific applications require the solution of large and sparse linear systems of equations us...