Add to ORKGWe discuss the application of sparse matrix approximations for two-grid and V-cycle multigrid methods. Sparse approximate inverses can be used as smoothers, further the Galerkin coarse matrix can be sparsified by sparse approximation techniques. Also the projection can be defined by combining sparse approximation with side conditions related to high frequency components. Numerical results are given, which demonstrate the efficiency and accuracy of the proposed strategies. © 2015 Elsevier Inc. All rights reserved
In this paper we discuss different possibilities of using partially ordered sets of grids in multigr...
. In this paper we discuss different possibilities of using partially ordered sets of grids in multi...
We give an overview of a number of algebraic multigrid methods targeting finite element discretizati...
AbstractThe multigrid W-cycle for the solution of sparse linear systems implemented with Galerkin sc...
Summary. Multigrid methods are among the fastest numerical algorithms for the solution of large spar...
Our goal is to present an elementary approach to the analysis and programming of sparse grid finite ...
Abstract. Various forms of sparse approximate inverses (SAI) have been shown to be useful for precon...
Sparse grids are a recently introduced new technique for discretizing partial differential equations...
Sparse grids have become an important tool to reduce the number of degrees of freedom of discretizat...
Multigrid methods are highly efficient solution techniques for large sparse linear systems which are...
In this thesis we study the approximate inverse based multigrid algorithm FAPIN for the solution of...
A sparse algebraic multigrid method is studied as a cheap and accurate way to compute approximations...
In undergraduates numerical mathematics courses I was strongly warned that inverting a matrix for co...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
In this paper we discuss different possibilities of using partially ordered sets of grids in multigr...
. In this paper we discuss different possibilities of using partially ordered sets of grids in multi...
We give an overview of a number of algebraic multigrid methods targeting finite element discretizati...
AbstractThe multigrid W-cycle for the solution of sparse linear systems implemented with Galerkin sc...
Summary. Multigrid methods are among the fastest numerical algorithms for the solution of large spar...
Our goal is to present an elementary approach to the analysis and programming of sparse grid finite ...
Abstract. Various forms of sparse approximate inverses (SAI) have been shown to be useful for precon...
Sparse grids are a recently introduced new technique for discretizing partial differential equations...
Sparse grids have become an important tool to reduce the number of degrees of freedom of discretizat...
Multigrid methods are highly efficient solution techniques for large sparse linear systems which are...
In this thesis we study the approximate inverse based multigrid algorithm FAPIN for the solution of...
A sparse algebraic multigrid method is studied as a cheap and accurate way to compute approximations...
In undergraduates numerical mathematics courses I was strongly warned that inverting a matrix for co...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
In this paper we discuss different possibilities of using partially ordered sets of grids in multigr...
. In this paper we discuss different possibilities of using partially ordered sets of grids in multi...
We give an overview of a number of algebraic multigrid methods targeting finite element discretizati...