Abstract

As the number of processors on supercomputers has increased dramatically, there is a growing interest in developing scalable algorithms with a high degree of parallelism for large-scale simulation. However, traditional simulators and algorithms for such nonlinear problems are usually based on the family of time-marching methods, where parallelization is restricted to the spatial dimension only. In this talk, we propose a family of parallel-in-time (PinT) algorithms for solving some large-scale flow problems from computational fluid dynamics or reservoir simulation, to fully exploit the parallelism of supercomputers.