Time May 4th,
Friday, 3-4pm
Location SB 111
Abstract
In this talk, we present a class of stabilized explicit-implicit domain decomposition (SEIDD) algorithms for parabolic equations. Explicit-implicit domain decomposition (EIDD) algorithms are globally non-iterative nonoverlapping domain decomposition methods, which, when compared with Schwartz algorithm based parabolic solvers, are both computationally and communicationally efficient for each time step simulation but suffer from time-step size restrictions due to conditional stability or conditional consistency. The stabilization in the SEIDD algorithms retain the time-stepwise efficiency in computation and communication of the EIDD algorithms but free the algorithms from time-step size restrictions, rendering SEIDD algorithms excellent candidates for large scale parallel simulation problems. Three algorithms of the SEIDD class are presented in this talk, which are mathematically analyzed and experimentally tested to show excellent stability, computation and communication efficiencies, and high parallel speedup and scalability.
Dr. Yu Zhuang received his Ph.D. computer science from Louisiana State University in Dec. 2000. He is currently a visiting assistant professor at IIT and will assume his assistant professorship in the CS dept of the Texas Technology University in August 2001.