Department of Computer Science
Shippensburg, PA 17257, USA
In solving systems of linear equations arising from practical scientific and engineering modeling and simulations such as electromagnetics applications, it is critical to choose a fast and robust solver. Due to the large scale of those problems, preconditioned Krylov subspace methods are most suitable. In electromagnetics simulations, the use of preconditioned Krylov subspace methods in the context of multilevel fast multipole algorithms (MLFMA) is particularly attractive. In this paper, we present a short survey on a few preconditioning techniques in this application. We also compare several preconditioning techniques combined with the Krylov subspace methods to solve large dense linear systems arising from electromagnetic scattering problems and present some numerical results.
Mathematics Subject Classification:
Technical Report 471-07, Department of Computer Science, University of Kentucky, Lexington, KY, 2007.
The research work of Zhang's research work was supported in part by the U.S National Science Foundation under grants CCR-0092532 and CCF-0527967, in part by the Kentucky Science and Engineering Foundation under grant KSEF-148-502-05-132, and in part by the Alzheimer's Association under a New Investigator Research Grant NIGR-06-25460.