ITERATIVE ILU PRECONDITIONERS FOR LINEAR SYSTEMS AND EIGENPROBLEMS
作者机构：ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Dipartimento di Matematica"F.Casorati"University of Pavia Via Ferrata 527100 PaviaItaly Dipartimento di MatematicaUniversity a di Paviavia Ferrata 527100 PaviaItaly School of Mathematical SciencesUniversity of Science and Technology of ChinaHefei 230026China Dipartimento di MatematicaUniversita di Paviavia Ferrata 527100 PaviaItaly
出 版 物：《Journal of Computational Mathematics》 (计算数学（英文）)
年 卷 期：2021年第39卷第4期
页 面：633-654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：The authors are members of the INdAM Research group GNCS and their research is partially supported by IMATI/CNR by PRIN/MIUR and the Dipartimenti di Eccellenza Program 2018-22-Dept of Mathematics University of Pavia
主 题：Iterative ILU factorization Matrix-matrix multiplication Fill-in Eigenvalue problem Parallel preconditioner
摘 要：Iterative ILU factorizations are constructed,analyzed and applied as preconditioners to solve both linear systems and *** computational kernels of these novel Iterative ILU factorizations are sparse matrix-matrix multiplications,which are easy and efficient to implement on both serial and parallel computer architectures and can take full advantage of existing matrix-matrix multiplication *** also introduce level-based and threshold-based algorithms in order to enhance the accuracy of the proposed Iterative ILU *** results of several numerical experiments illustrate the efficiency of the proposed preconditioners to solve both linear systems and eigenvalue problems.
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