Sparse approximate inverse smoothers for geometric and algebraic multigrid

Sparse Approximate Inverse Smoothers For Geometric and Algebraic Multigrid

Sparse Approximate Inverse Smoothers For Geometric and Algebraic Multigrid

Parallel Smoothers Using Sparse Approximate Inverse

Sparse approximate inverses' usefulness in a parallel environment has motivated much interest in recent years. However, the superior capability of an approximate inverse in eliminating the local error has not yet been fully exploited in multi-grid algorithms. We propose a new class of sparse approximate inverse smoothers in this paper and present their analytic smoothing factors for constant co...

Sparse Approximate Inverse Smoother for Multigrid

Various forms of sparse approximate inverses (SAI) have been shown to be useful for preconditioning. Their potential usefulness in a parallel environment has motivated much interest in recent years. However, the capability of an approximate inverse in eliminating the local error has not yet been fully exploited in multigrid algorithms. A careful examination of the iteration matrices of these ap...

A hybrid geometric + algebraic multigrid method with semi-iterative smoothers

We propose a multigrid method for solving large-scale sparse linear systems arising from discretizations of partial differential equations, such as those from finite element and generalized finite difference (GFD) methods. Our proposed method has the following two characteristics. First, we introduce a hybrid geometric+algebraic multigrid method, or HyGA, to leverage the rigor, accuracy and eff...