鞍点线性系统序列的预条件更新

IF 0.3 Q4 MATHEMATICS Communications in Applied and Industrial Mathematics Pub Date : 2018-02-01 DOI:10.1515/caim-2018-0003

V. Simone, D. Serafino, B. Morini

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引用次数: 6

摘要

摘要通过Krylov方法更新求解大型稀疏鞍点线性系统序列的预处理算子，在过去几年中受到了越来越多的关注，因为它可以降低预处理的成本，同时保持整个求解过程的效率。本文简要介绍了文献中针对这一问题提出的两种方法：更新块LDLT形式的预处理器的因子，以及通过受准牛顿方法启发的有限记忆技术更新预处理器。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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On preconditioner updates for sequences of saddle-point linear systems

Abstract Updating preconditioners for the solution of sequences of large and sparse saddle- point linear systems via Krylov methods has received increasing attention in the last few years, because it allows to reduce the cost of preconditioning while keeping the efficiency of the overall solution process. This paper provides a short survey of the two approaches proposed in the literature for this problem: updating the factors of a preconditioner available in a block LDLT form, and updating a preconditioner via a limited-memory technique inspired by quasi-Newton methods.

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来源期刊

Communications in Applied and Industrial Mathematics Mathematics-Applied Mathematics

CiteScore

1.30

自引率

0.00%

发文量

审稿时长

16 weeks

期刊介绍： Communications in Applied and Industrial Mathematics (CAIM) is one of the official journals of the Italian Society for Applied and Industrial Mathematics (SIMAI). Providing immediate open access to original, unpublished high quality contributions, CAIM is devoted to timely report on ongoing original research work, new interdisciplinary subjects, and new developments. The journal focuses on the applications of mathematics to the solution of problems in industry, technology, environment, cultural heritage, and natural sciences, with a special emphasis on new and interesting mathematical ideas relevant to these fields of application . Encouraging novel cross-disciplinary approaches to mathematical research, CAIM aims to provide an ideal platform for scientists who cooperate in different fields including pure and applied mathematics, computer science, engineering, physics, chemistry, biology, medicine and to link scientist with professionals active in industry, research centres, academia or in the public sector. Coverage includes research articles describing new analytical or numerical methods, descriptions of modelling approaches, simulations for more accurate predictions or experimental observations of complex phenomena, verification/validation of numerical and experimental methods; invited or submitted reviews and perspectives concerning mathematical techniques in relation to applications, and and fields in which new problems have arisen for which mathematical models and techniques are not yet available.