Parallel preconditioners for solutions of dense linear systems with tens of millions of unknowns
buir.contributor.author | Gürel, Levent | |
buir.contributor.author | Ergül, Özgür | |
dc.citation.epage | 402 | en_US |
dc.citation.spage | 399 | en_US |
dc.contributor.author | Malas, Tahir | en_US |
dc.contributor.author | Ergül, Özgür | en_US |
dc.contributor.author | Gürel, Levent | en_US |
dc.coverage.spatial | Ankara, Turkey | |
dc.date.accessioned | 2016-02-08T11:43:28Z | |
dc.date.available | 2016-02-08T11:43:28Z | |
dc.date.issued | 2007-11 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.department | Computational Electromagnetics Research Center (BiLCEM) | en_US |
dc.description | Date of Conference: 7-9 Nov. 2007 | |
dc.description | Conference name: 22nd international symposium on computer and information sciences, 2007 | |
dc.description.abstract | We propose novel parallel preconditioning schemes for the iterative solution of integral equation methods. In particular, we try to improve convergence rate of the ill-conditioned linear systems formulated by the electric-field integral equation, which is the only integral-equation formulation for targets having open surfaces. For moderate-size problems, iterative solution of the near-field system enables much faster convergence compared to the widely used sparse approximate inverse preconditioner. For larger systems, we propose an approximation strategy to the multilevel fast multipole algorithm (MLFMA) to be used as a preconditioner. Our numerical experiments reveal that this scheme significantly outperforms other preconditioners. With the combined effort of effective preconditioners and an efficiently parallelized MLFMA, we are able to solve targets with tens of millions of unknowns, which are the largest problems ever reported in computational electromagnetics. ©2007 IEEE. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T11:43:28Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2007 | en |
dc.identifier.doi | 10.1109/ISCIS.2007.4456895 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/27069 | |
dc.language.iso | English | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/ISCIS.2007.4456895 | en_US |
dc.source.title | 22nd International Symposium on Computer and Information Sciences, ISCIS 2007 - Proceedings | en_US |
dc.subject | Approximation algorithms | en_US |
dc.subject | Boundary element method | en_US |
dc.subject | Communication | en_US |
dc.subject | Cybernetics | en_US |
dc.subject | Eigenvalues and eigenfunctions | en_US |
dc.subject | Electromagnetism | en_US |
dc.subject | Information management | en_US |
dc.subject | Information science | en_US |
dc.subject | Inverse problems | en_US |
dc.subject | Iterative methods | en_US |
dc.subject | Linear equations | en_US |
dc.subject | Linear systems | en_US |
dc.subject | Magnetism | en_US |
dc.subject | Radar antennas | en_US |
dc.subject | Solutions | en_US |
dc.subject | Computational electromagnetics (CEM) | en_US |
dc.subject | Convergence rates | en_US |
dc.subject | Faster convergence | en_US |
dc.subject | Field integral | en_US |
dc.subject | Integral Equation Method (IEM) | en_US |
dc.subject | Integral-equation | en_US |
dc.subject | International symposium | en_US |
dc.subject | Iterative solutions | en_US |
dc.subject | Multilevel fast multipole algorithm (MLFMA) | en_US |
dc.subject | Near fields | en_US |
dc.subject | Numerical experiments | en_US |
dc.subject | Open surfaces | en_US |
dc.subject | Parallel preconditioners | en_US |
dc.subject | Parallel preconditioning | en_US |
dc.subject | Preconditioner | en_US |
dc.subject | Preconditioners | en_US |
dc.subject | Sparse approximate inverse (SAI) | en_US |
dc.subject | Integral equations | en_US |
dc.title | Parallel preconditioners for solutions of dense linear systems with tens of millions of unknowns | en_US |
dc.type | Conference Paper | en_US |
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