Scalable parallelization of the sparse-approximate-inverse (SAl) preconditioner for the solution of large-scale integral-equation problems

dc.citation.epage4en_US
dc.citation.spage1en_US
dc.contributor.authorMalas, Tahiren_US
dc.contributor.authorGürel, Leventen_US
dc.contributor.bilkentauthorGürel, Levent
dc.coverage.spatialCharleston, SC, USA
dc.date.accessioned2016-02-08T12:27:16Z
dc.date.available2016-02-08T12:27:16Z
dc.date.issued2009-06en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.departmentComputational Electromagnetics Research Center (BiLCEM)en_US
dc.descriptionDate of Conference: 1-5 June 2009
dc.descriptionConference name: 2009 IEEE Antennas and Propagation Society International Symposium
dc.description.abstractIn this paper, we consider efficient parallelization of the sparse approximate inverse (SAI) preconditioner in the context of the multilevel fast multipole algorithm (MLFMA). Then, we report the use of SAI in the solution of very large EFIE problems. The SAI preconditioner is important not only because it is a robust preconditioner that renders many difficult and large problems solvable, but also it can be utilized for the construction of more effective preconditioners.en_US
dc.identifier.doi10.1109/APS.2009.5172284en_US
dc.identifier.issn1522-3965
dc.identifier.urihttp://hdl.handle.net/11693/28690
dc.language.isoEnglishen_US
dc.publisherIEEE
dc.relation.isversionofhttp://dx.doi.org/10.1109/APS.2009.5172284en_US
dc.source.titleIEEE Antennas and Propagation Society, AP-S International Symposium (Digest)en_US
dc.subjectLarge-scale systems
dc.subjectCosts
dc.subjectEar
dc.subjectRobustness
dc.subjectMLFMA
dc.subjectPartitioning algorithms
dc.subjectComputational electromagnetics
dc.subjectElectromagnetic scattering
dc.subjectIntegral equations
dc.subjectConcurrent computing
dc.titleScalable parallelization of the sparse-approximate-inverse (SAl) preconditioner for the solution of large-scale integral-equation problemsen_US
dc.typeConference Paperen_US
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