报 告 题 目：Robustness and Adaptivity of Iterative Solvers

主 讲 人：张 晨 松

单 位：中国科学院数学与系统科学研究院

时 间：10月25日14:00

腾 讯 ID：936-658-135

摘 要：

Linear systems arising from coupled PDEs in multiphysics applications could cause robustness problems for iterative solution methods. Solving large-scale linear algebraic systems in an efficient and robust manner is a dream for many computational scientists who work on practical engineering applications. In this talk, we review some old and new techniques for improving the robustness of iterative solvers for large-scale sparse linear equations. In particular, we will discuss methods based on machine learning to select solver components automatically to improve overall simulation performance. Based on this algorithm selection model, a self-adaptive procedure can be derived to improve the robustness of iterative solvers.

简 介：

Chen-Song Zhang, PhD. Graduated from the Applied Mathematics & Scientific Computing program at the University of Maryland, College Park, US; Worked as a postdoctoral fellow at the Penn State University, University Park, US; Currently working at the Academy of Mathematics and Systems Science, CAS, China. Main research interests include numerical analysis, adaptive methods, petroleum reservoir simulation, and complex fluid/flow simulation.