We introduce a coarsening algorithm for algebraic multigrid (AMG) based on the concept of compatible relaxation (CR). The algorithm is significantly different from standard methods, most notably because it does not rely on any notion of strength of connection. We study its behavior on a number of model problems, and evaluate the performance of an AMG algorithm that incorporates the coarsening approach. Lastly, we introduce a variant of CR that provides a sharper metric of coarse-grid quality and demonstrate its potential with two simple examples
160 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.The experimental results moti...
160 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.The experimental results moti...
. An algebraic multigrid algorithm for symmetric, positive definite linear systems is developed base...
We present a theory for algebraic multigrid (AMG) methods that allows for general smoothing processe...
Algebraic multigrid (AMG) is an iterative method that is often optimal for solving the matrix equati...
We give an overview of a number of algebraic multigrid methods targeting finite element discretizati...
We describe main issues and design principles of an efficient implementation, tailored to recent gen...
The need to solve linear systems arising from problems posed on extremely large, unstructured grids ...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...
Solving partial differential equations (PDEs) using analytical techniques is intractable for all but...
The Algebraic Multigrid (AMG) method has over the years developed into an ecient tool for solving un...
Algebraic Multigrid (AMG) is an efficient multigrid method for solving large problems, using only th...
AbstractThe convergence theory for algebraic multigrid (AMG) algorithms proposed in Chang and Huang ...
Multigrid methods are often the most efficient approaches for solving the very large linear systems...
Multigrid methods are often the most efficient approaches for solving the very large linear systems...
160 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.The experimental results moti...
160 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.The experimental results moti...
. An algebraic multigrid algorithm for symmetric, positive definite linear systems is developed base...
We present a theory for algebraic multigrid (AMG) methods that allows for general smoothing processe...
Algebraic multigrid (AMG) is an iterative method that is often optimal for solving the matrix equati...
We give an overview of a number of algebraic multigrid methods targeting finite element discretizati...
We describe main issues and design principles of an efficient implementation, tailored to recent gen...
The need to solve linear systems arising from problems posed on extremely large, unstructured grids ...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...
Solving partial differential equations (PDEs) using analytical techniques is intractable for all but...
The Algebraic Multigrid (AMG) method has over the years developed into an ecient tool for solving un...
Algebraic Multigrid (AMG) is an efficient multigrid method for solving large problems, using only th...
AbstractThe convergence theory for algebraic multigrid (AMG) algorithms proposed in Chang and Huang ...
Multigrid methods are often the most efficient approaches for solving the very large linear systems...
Multigrid methods are often the most efficient approaches for solving the very large linear systems...
160 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.The experimental results moti...
160 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.The experimental results moti...
. An algebraic multigrid algorithm for symmetric, positive definite linear systems is developed base...