A Parallel Refined Jacobi-Davidson Method for Quadratic Eigenvalue Problems
This paper presents a parallel refined Jacobi-Davidson method for computing extreme eigenpairs of quadratic eigenvalue problems. The method directly computes the refined Ritz pairs in the projection subspace, and expands the subspace by the solution of the correction equation. Combining with the res...
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| creator | Shunxu Wang |
| description | This paper presents a parallel refined Jacobi-Davidson method for computing extreme eigenpairs of quadratic eigenvalue problems. The method directly computes the refined Ritz pairs in the projection subspace, and expands the subspace by the solution of the correction equation. Combining with the restarting scheme, the method can solve several eigenpairs of quadratic eigenvalue problems. The numerical experiments on a parallel computer show that the parallel refined Jacobi-Davidson method for computing quadratic eigenvalue problems is very effective. |
| doi_str_mv | 10.1109/PAAP.2010.62 |
| format | Conference Proceeding |
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The method directly computes the refined Ritz pairs in the projection subspace, and expands the subspace by the solution of the correction equation. Combining with the restarting scheme, the method can solve several eigenpairs of quadratic eigenvalue problems. The numerical experiments on a parallel computer show that the parallel refined Jacobi-Davidson method for computing quadratic eigenvalue problems is very effective.</description><identifier>ISSN: 2168-3034</identifier><identifier>ISBN: 1424494826</identifier><identifier>ISBN: 9781424494828</identifier><identifier>DOI: 10.1109/PAAP.2010.62</identifier><identifier>LCCN: 2010937795</identifier><language>eng</language><publisher>IEEE</publisher><subject>Approximation methods ; Eigenvalues and eigenfunctions ; Equations ; Integrated circuits ; Jacobi-Davidson method ; Jacobian matrices ; Matrix decomposition ; Parallel algorithm ; Parallel processing ; Quadratic eigenvalue problems ; Refined method</subject><ispartof>2010 3rd International Symposium on Parallel Architectures, Algorithms and Programming, 2010, p.111-115</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5715071$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2051,27904,54898</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5715071$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Shunxu Wang</creatorcontrib><title>A Parallel Refined Jacobi-Davidson Method for Quadratic Eigenvalue Problems</title><title>2010 3rd International Symposium on Parallel Architectures, Algorithms and Programming</title><addtitle>paap</addtitle><description>This paper presents a parallel refined Jacobi-Davidson method for computing extreme eigenpairs of quadratic eigenvalue problems. The method directly computes the refined Ritz pairs in the projection subspace, and expands the subspace by the solution of the correction equation. Combining with the restarting scheme, the method can solve several eigenpairs of quadratic eigenvalue problems. The numerical experiments on a parallel computer show that the parallel refined Jacobi-Davidson method for computing quadratic eigenvalue problems is very effective.</description><subject>Approximation methods</subject><subject>Eigenvalues and eigenfunctions</subject><subject>Equations</subject><subject>Integrated circuits</subject><subject>Jacobi-Davidson method</subject><subject>Jacobian matrices</subject><subject>Matrix decomposition</subject><subject>Parallel algorithm</subject><subject>Parallel processing</subject><subject>Quadratic eigenvalue problems</subject><subject>Refined method</subject><issn>2168-3034</issn><isbn>1424494826</isbn><isbn>9781424494828</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjMtOwkAUQCdREgHZuXMzP1Cc92PZIOIDYzXsyW3njo4p1EwLiX8vRlcnJzk5hFxxNuec-ZuqLKu5YCc14oxMuBJKeeWEOSdjwY0rJJNqRCa_iZfWen1BZn3_yRiT3Hln2Jg8lbSCDG2LLX3DmPYY6CM0XZ2KWzim0Hd7-ozDRxdo7DJ9PUDIMKSGLtM77o_QHpBWuatb3PWXZBSh7XH2zynZ3C03i_ti_bJ6WJTrInk2FFpb8GBRKaeDtGi0PdHVFhAMc7xxPgYVvWPSeiFNECaKCEJbq2sdg5yS679tQsTtV047yN9bbblmlssf4m9NRQ</recordid><startdate>201012</startdate><enddate>201012</enddate><creator>Shunxu Wang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201012</creationdate><title>A Parallel Refined Jacobi-Davidson Method for Quadratic Eigenvalue Problems</title><author>Shunxu Wang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-557a9a7e4485d37e6575d38b7aea6081c89fd4f980379236d26f2fa25775b5fd3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Approximation methods</topic><topic>Eigenvalues and eigenfunctions</topic><topic>Equations</topic><topic>Integrated circuits</topic><topic>Jacobi-Davidson method</topic><topic>Jacobian matrices</topic><topic>Matrix decomposition</topic><topic>Parallel algorithm</topic><topic>Parallel processing</topic><topic>Quadratic eigenvalue problems</topic><topic>Refined method</topic><toplevel>online_resources</toplevel><creatorcontrib>Shunxu Wang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Shunxu Wang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A Parallel Refined Jacobi-Davidson Method for Quadratic Eigenvalue Problems</atitle><btitle>2010 3rd International Symposium on Parallel Architectures, Algorithms and Programming</btitle><stitle>paap</stitle><date>2010-12</date><risdate>2010</risdate><spage>111</spage><epage>115</epage><pages>111-115</pages><issn>2168-3034</issn><isbn>1424494826</isbn><isbn>9781424494828</isbn><abstract>This paper presents a parallel refined Jacobi-Davidson method for computing extreme eigenpairs of quadratic eigenvalue problems. The method directly computes the refined Ritz pairs in the projection subspace, and expands the subspace by the solution of the correction equation. Combining with the restarting scheme, the method can solve several eigenpairs of quadratic eigenvalue problems. The numerical experiments on a parallel computer show that the parallel refined Jacobi-Davidson method for computing quadratic eigenvalue problems is very effective.</abstract><pub>IEEE</pub><doi>10.1109/PAAP.2010.62</doi><tpages>5</tpages></addata></record> |
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| ispartof | 2010 3rd International Symposium on Parallel Architectures, Algorithms and Programming, 2010, p.111-115 |
| issn | 2168-3034 |
| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Approximation methods Eigenvalues and eigenfunctions Equations Integrated circuits Jacobi-Davidson method Jacobian matrices Matrix decomposition Parallel algorithm Parallel processing Quadratic eigenvalue problems Refined method |
| title | A Parallel Refined Jacobi-Davidson Method for Quadratic Eigenvalue Problems |
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