Preconditioning Schur Complement Systems of Highly-Indefinite Linear Systems for a Parallel Hybrid Solver

作     者：I.Yamazaki E.G.Ng 

作者机构：Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA 

出 版 物：《Numerical Mathematics(Theory,Methods and Applications)》 (高等学校计算数学学报（英文版）)

年 卷 期：2010年第3卷第3期

页      面：352-366页

核心收录：

学科分类：07[理学] 070102[理学-计算数学] 0701[理学-数学] 

基　　金：supported in part by the Director Office of Science Office of Advanced Scientific Computing Research of the U.S.Department of Energy under Contract No.DE-AC02-05CH11231 

主　　题：Schur complement method preconditioning matrix preprocessing. 

摘      要：A parallel hybrid linear solver based on the Schur complement method has the potential to balance the robustness of direct solvers with the efficiency of preconditioned iterative ***,when solving large-scale highly-indefinite linear systems,this hybrid solver often suffers from either slow convergence or large memory requirements to solve the Schur complement *** overcome this challenge,we in this paper discuss techniques to preprocess the Schur complement systems in parallel. Numerical results of solving large-scale highly-indefinite linear systems from various applications demonstrate that these techniques improve the reliability and performance of the hybrid solver and enable efficient solutions of these linear systems on hundreds of processors,which was previously infeasible using existing state-of-the-art solvers.