The E² Bathe subspace iteration method

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019 === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 91-93). === Since its development in 1971, the Bathe subspace iteration method has been widely-used to solve the ge...

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Main Author: Wilkins, Bryce Daniel.
Other Authors: Klaus-Jürgen Bathe and Mavis Driscoll.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2019
Subjects:
Online Access:https://hdl.handle.net/1721.1/122238
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-1222382019-11-23T03:51:08Z The E² Bathe subspace iteration method Enriched-Enriched Bathe subspace iteration method Wilkins, Bryce Daniel. Klaus-Jürgen Bathe and Mavis Driscoll. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering Mechanical Engineering. Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019 Cataloged from PDF version of thesis. Includes bibliographical references (pages 91-93). Since its development in 1971, the Bathe subspace iteration method has been widely-used to solve the generalized symmetric-definite eigenvalue problem. The method is particularly useful for solving large eigenvalue problems when only a few of the least dominant eigenpairs are sought. In reference [18], an enriched subspace iteration method was proposed that accelerated the convergence of the basic method by replacing some of the iteration vectors with more effective turning vectors. In this thesis, we build upon this recent acceleration effort and further enrich the subspace of each iteration by replacing additional iteration vectors with our new turning-of-turning vectors. We begin by reviewing the underpinnings of the subspace iteration methodology. Then, we present the steps of our new algorithm, which we refer to as the Enriched- Enriched (E2 ) Bathe subspace iteration method. This is followed by a tabulation of the number of floating point operations incurred during a general iteration of the E2 algorithm. Additionally, we perform a simplified convergence analysis showing that the E2 method converges asymptotically at a faster rate than the enriched method. Finally, we examine the results from several test problems that were used to illustrate the E2 method and to assess its potential computational savings compared to the enriched method. The sample results for the E2 method are consistent with the theoretical asymptotic convergence rate that was obtained in our convergence analysis. Further, the results from the CPU time tests suggest that the E2 method can often provide a useful reduction in computational effort compared to the enriched method, particularly when relatively few iteration vectors are used in comparison with the number of eigenpairs that are sought. by Bryce Daniel Wilkins. S.M. S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering 2019-09-17T19:49:27Z 2019-09-17T19:49:27Z 2019 2019 Thesis https://hdl.handle.net/1721.1/122238 1119389008 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 93 pages application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Mechanical Engineering.
spellingShingle Mechanical Engineering.
Wilkins, Bryce Daniel.
The E² Bathe subspace iteration method
description Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019 === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 91-93). === Since its development in 1971, the Bathe subspace iteration method has been widely-used to solve the generalized symmetric-definite eigenvalue problem. The method is particularly useful for solving large eigenvalue problems when only a few of the least dominant eigenpairs are sought. In reference [18], an enriched subspace iteration method was proposed that accelerated the convergence of the basic method by replacing some of the iteration vectors with more effective turning vectors. In this thesis, we build upon this recent acceleration effort and further enrich the subspace of each iteration by replacing additional iteration vectors with our new turning-of-turning vectors. We begin by reviewing the underpinnings of the subspace iteration methodology. Then, we present the steps of our new algorithm, which we refer to as the Enriched- Enriched (E2 ) Bathe subspace iteration method. This is followed by a tabulation of the number of floating point operations incurred during a general iteration of the E2 algorithm. Additionally, we perform a simplified convergence analysis showing that the E2 method converges asymptotically at a faster rate than the enriched method. Finally, we examine the results from several test problems that were used to illustrate the E2 method and to assess its potential computational savings compared to the enriched method. The sample results for the E2 method are consistent with the theoretical asymptotic convergence rate that was obtained in our convergence analysis. Further, the results from the CPU time tests suggest that the E2 method can often provide a useful reduction in computational effort compared to the enriched method, particularly when relatively few iteration vectors are used in comparison with the number of eigenpairs that are sought. === by Bryce Daniel Wilkins. === S.M. === S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering
author2 Klaus-Jürgen Bathe and Mavis Driscoll.
author_facet Klaus-Jürgen Bathe and Mavis Driscoll.
Wilkins, Bryce Daniel.
author Wilkins, Bryce Daniel.
author_sort Wilkins, Bryce Daniel.
title The E² Bathe subspace iteration method
title_short The E² Bathe subspace iteration method
title_full The E² Bathe subspace iteration method
title_fullStr The E² Bathe subspace iteration method
title_full_unstemmed The E² Bathe subspace iteration method
title_sort e² bathe subspace iteration method
publisher Massachusetts Institute of Technology
publishDate 2019
url https://hdl.handle.net/1721.1/122238
work_keys_str_mv AT wilkinsbrycedaniel thee2bathesubspaceiterationmethod
AT wilkinsbrycedaniel enrichedenrichedbathesubspaceiterationmethod
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