An Aggregation-Based Algebraic Multigrid Method with Deflation Techniques and Modified Generic Factored Approximate Sparse Inverses

In this paper, we examine deflation-based algebraic multigrid methods for solving large systems of linear equations. Aggregation the unknown terms is applied coarsening, while deflation techniques are proposed improving rate convergence. More specifically, V-cycle strategy adopted, in which, at each iteration, solution computed by initially decomposing it utilizing two complementary subspaces. The approximate formed combining obtained using multigrids and deflation. order to improve performance convergence behavior, scheme was coupled with Modified Generic Factored Approximate Sparse Inverse preconditioner. Furthermore, a parallel version multicore systems, techniques. Finally, characteristic model problems solved demonstrate applicability schemes, numerical results given.