Comparison of partitioning strategies for PDE solvers on multiblock grids
Different partitioning strategies for multiblock grids have been compared experimentally. The numerical experiments have been performed on a 512 processor Cray T3D using a compressible two dimensional Navier-Stokes solver. Some complementary results are made with an advection equation solver using a...
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description | Different partitioning strategies for multiblock grids have been compared experimentally. The numerical experiments have been performed on a 512 processor Cray T3D using a compressible two dimensional Navier-Stokes solver. Some complementary results are made with an advection equation solver using a Cray T3E-900. The results show that the behavior of the different parallelization strategies depends very much on the number of subgrids and their sizes as well as the number of available processors. In order to get optimal performance for a certain problem and processor configuration, the partitioning strategy must be chosen with regard to these aspects. Our results give guidelines for this. |
doi_str_mv | 10.1007/BFb0095370 |
format | Conference Proceeding |
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The numerical experiments have been performed on a 512 processor Cray T3D using a compressible two dimensional Navier-Stokes solver. Some complementary results are made with an advection equation solver using a Cray T3E-900. The results show that the behavior of the different parallelization strategies depends very much on the number of subgrids and their sizes as well as the number of available processors. In order to get optimal performance for a certain problem and processor configuration, the partitioning strategy must be chosen with regard to these aspects. 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The numerical experiments have been performed on a 512 processor Cray T3D using a compressible two dimensional Navier-Stokes solver. Some complementary results are made with an advection equation solver using a Cray T3E-900. The results show that the behavior of the different parallelization strategies depends very much on the number of subgrids and their sizes as well as the number of available processors. In order to get optimal performance for a certain problem and processor configuration, the partitioning strategy must be chosen with regard to these aspects. Our results give guidelines for this.</description><subject>Applied sciences</subject><subject>Block Partitioning</subject><subject>Composite Grid</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Load Balance</subject><subject>Miscellaneous</subject><subject>Parallelization Strategy</subject><subject>Partitioning Strategy</subject><subject>Software</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>3540654143</isbn><isbn>9783540654148</isbn><isbn>3540492615</isbn><isbn>9783540492610</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNpFkEtLAzEUheMLrLUbf0EWLgQZTSavybL2oYWCLtRtSKbJEDudDMmM4r93pEUvF-6B892zOABcYXSHERL3D0uDkGREoCNwQRhFVOYcs2MwwhzjjBAqT_YGZxRTcgpGiKA8k4KSczBJ6QMNQ3JMmByB1SzsWh19Cg0MDg6y850PjW8qmLqoO1t5m6ALEb7MFzCF-tPGBAd619edN3Uot7CKfpMuwZnTdbKTwx2Dt-XidfaUrZ8fV7PpOmsxL0SWF5bSQhY8F5ThghLOLBeiKBwvOdsQvEGmlBtqpMO5FJY5YZ1GgjotjUGGjMHtPjd92bY3qo1-p-O3CtqruX-fqhAr1fcqF2TYMbje061Opa5d1E3p098TZoIijAfs5hA6OE1lozIhbJPCSP2Wrv5LJz-cfG68</recordid><startdate>20061020</startdate><enddate>20061020</enddate><creator>Rantakokko, Jarmo</creator><general>Springer Berlin Heidelberg</general><general>Springer-Verlag</general><scope>IQODW</scope><scope>ADTPV</scope><scope>BNKNJ</scope><scope>DF2</scope></search><sort><creationdate>20061020</creationdate><title>Comparison of partitioning strategies for PDE solvers on multiblock grids</title><author>Rantakokko, Jarmo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p1687-28e4489862745184365e67788f6c65d31d0bc9d4b9f1297e5f7efa074fa9bb0b3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Applied sciences</topic><topic>Block Partitioning</topic><topic>Composite Grid</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Load Balance</topic><topic>Miscellaneous</topic><topic>Parallelization Strategy</topic><topic>Partitioning Strategy</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rantakokko, Jarmo</creatorcontrib><collection>Pascal-Francis</collection><collection>SwePub</collection><collection>SwePub Conference</collection><collection>SWEPUB Uppsala universitet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rantakokko, Jarmo</au><au>Waśniewski, Jerzy</au><au>Dongarra, Jack</au><au>Elmroth, Erik</au><au>Kågström, Bo</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Comparison of partitioning strategies for PDE solvers on multiblock grids</atitle><btitle>Applied Parallel Computing</btitle><date>2006-10-20</date><risdate>2006</risdate><spage>468</spage><epage>475</epage><pages>468-475</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>3540654143</isbn><isbn>9783540654148</isbn><eisbn>3540492615</eisbn><eisbn>9783540492610</eisbn><abstract>Different partitioning strategies for multiblock grids have been compared experimentally. The numerical experiments have been performed on a 512 processor Cray T3D using a compressible two dimensional Navier-Stokes solver. Some complementary results are made with an advection equation solver using a Cray T3E-900. The results show that the behavior of the different parallelization strategies depends very much on the number of subgrids and their sizes as well as the number of available processors. In order to get optimal performance for a certain problem and processor configuration, the partitioning strategy must be chosen with regard to these aspects. Our results give guidelines for this.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/BFb0095370</doi><tpages>8</tpages></addata></record> |
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language | eng |
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source | Springer Books |
subjects | Applied sciences Block Partitioning Composite Grid Computer science control theory systems Exact sciences and technology Load Balance Miscellaneous Parallelization Strategy Partitioning Strategy Software |
title | Comparison of partitioning strategies for PDE solvers on multiblock grids |
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