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.

Short bio

杨海建，教授，博士生导师。主要从事与大规模并行计算相关的数学建模、基础算法和应用研究。围绕这一研究方向，在计算流体力学、全球大气模式和油藏模拟等应用领域选择有代表性意义的典型问题开展科学计算研究，以第一作者或通讯作者在SISC、JCP、CMAME、CPC等数学SCI期刑发表论文三十余篇。