Scalable Parallel Solvers for Multiphysics Problems

Xiao-Chuan Cai
University of Colorado at Boulder

In this talk, we discuss some recent development of scalable parallel
algorithms for solving large scale linear and nonlinear systems
arising from the discretization of a wide range of multiphysics
problems. These techniques are based on a combination of domain
decomposition and multigrid methods, both have been well studied for
linear elliptic type problems.  The focus of this talk is on the
extensions and modifications of these methods to some much harder
multiphysics problems, such as magnetodydrodynamics, boundary control
of Navier-Stokes equations, bio-fluid dynamics, and parameter
identification problems. Scalabilities results obtained on
supercomputers with large number of processors will be presented.

Brief Biography:
Xiao-Chuan Cai is a Professor of Computer Science at the University of
Colorado at Boulder. He received his PhD from Courant Institute of
Mathematical Sciences, New York University, in 1989. His research
interests include parallel algorithms and high performance software
for numerical solution of partial differential equations, domain
decomposition methods, multigrid methods, numerical linear algebra,
PDE constrained optimization, inverse problems, stochastic partial
differential equations, computational fluid dynamics, computational
plasma physics, and computational biomechanics.