Robust algorithms and software for parallel PDE-based simulations

component software, multimethod solvers The solution of nonlinear partial differential equations (PDEs), such as those arising in computational fluid dy-namics, forms an important class of applications in sci-entific computing. Simulation times typically depend to a large extent on the robustness and efficiency of the sparse linear solver used at each iteration of the nonlinear PDE solver. We consider algorithms and software to develop ro-bust and efficient solvers as composites of multiple precon-ditioned iterative methods. Iterative solvers allow scalable parallel implementation but can often converge slowly or fail to converge. Our methods address this deficiency by using a sequence of iterative methods to provide a highly reliable solution with good parallel performance. We de-scribe our algorithms and software for instantiating such multimethod composite solvers and report on their perfor-mance in a driven cavity flow application.