Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances

arXiv:2310.02246v2 Announce Type: replace
Abstract: Solving a linear system $Ax=b$ is a fundamental scientific computing primitive for which numerous solvers and preconditioners have been developed. These come with parameters whose optimal values depend on the system being solved and are often impossible or too expensive to identify; thus in practice sub-optimal heuristics are used. We consider the common setting in which many related linear systems need to be solved, e.g. during a single numerical simulation. In this scenario, can we …

abstract arxiv computing cs.ai cs.lg cs.na fundamental identify instances linear math.na parameters scientific solver stat.ml type values