BootCMatch. A software package for bootstrap AMG based on graph weighted matching. This article has two main objectives: one is to describe some extensions of an adaptive Algebraic Multigrid (AMG) method of the form previously proposed by the first and third authors, and a second one is to present a new software framework, named BootCMatch, which implements all the components needed to build and apply the described adaptive AMG both as a stand-alone solver and as a preconditioner in a Krylov method. The adaptive AMG presented is meant to handle general symmetric and positive definite (SPD) sparse linear systems, without assuming any a priori information of the problem and its origin; the goal of adaptivity is to achieve a method with a prescribed convergence rate. The presented method exploits a general coarsening process based on aggregation of unknowns, obtained by a maximum weight matching in the adjacency graph of the system matrix. More specifically, a maximum product matching is employed to define an effective smoother subspace (complementary to the coarse space), a process referred to as compatible relaxation, at every level of the recursive two-level hierarchical AMG process. Results on a large variety of test cases and comparisons with related work demonstrate the reliability and efficiency of the method and of the software.
Keywords for this software
References in zbMATH (referenced in 7 articles , 1 standard article )
Showing results 1 to 7 of 7.
- Massimo Bernaschi, Pasqua D’Ambra, Dario Pasquini: BootCMatchG: An adaptive Algebraic MultiGrid linear solver for GPUs (2020) not zbMATH
- Sashikumaar Ganesan, Manan Shah: SParSH-AMG: A library for hybrid CPU-GPU algebraic multigrid and preconditioned iterative methods (2020) arXiv
- D’Ambra, Pasqua; Vassilevski, Panayot S.: Improving solve time of aggregation-based adaptive AMG. (2019)
- Franceschini, Andrea; Paludetto Magri, Victor A.; Mazzucco, Gianluca; Spiezia, Nicolò; Janna, Carlo: A robust adaptive algebraic multigrid linear solver for structural mechanics (2019)
- Paludetto Magri, Victor A.; Franceschini, Andrea; Janna, Carlo: A novel algebraic multigrid approach based on adaptive smoothing and prolongation for ill-conditioned systems (2019)
- Abdullahi, Ambra; D’Ambra, Pasqua; Di Serafino, Daniela; Filippone, Salvatore: Parallel aggregation based on compatible weighted matching for AMG (2018)
- D’ambra, Pasqua; Filippone, Salvatore; Vassilevski, Panayot S.: BootCMatch. A software package for bootstrap AMG based on graph weighted matching (2018)