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dc.contributor.authorSun, Chunguangen_US
dc.date.accessioned2007-04-03T14:43:01Z
dc.date.available2007-04-03T14:43:01Z
dc.date.issued1992-08en_US
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.tc/92-102en_US
dc.identifier.urihttps://hdl.handle.net/1813/5478
dc.description.abstractWe consider several issues involved in the solution of sparse symmetric positive definite system by multifrontal method on distributed-memory multiprocessors. First, we present a new algorithm for computing the partial factorization of a frontal matrix on a subset of processors which significantly improves the performance of a distributed multifrontal algorithm previously designed. Second, new parallel algorithms for computing sparse forward elimination and sparse backward substitution are described. The new algorithms solve the sparse triangular systems in multi- frontal fashion. Numerical experiments run on an Intel iPSC/860 and an Intel iPSC/2 for a set of problems with regular and irregular sparsity structure are reported. More than 180 million flops per second during the numerical factorization are achieved for a three- dimensional grid problem on an iPSC/860 machine with 32 processors.en_US
dc.format.extent233287 bytes
dc.format.extent220962 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjecttheory centeren_US
dc.titleEfficient Parallel Solutions of Large Sparse SPD Systems on Distributed-memory Multiprocessorsen_US
dc.typetechnical reporten_US


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