Communication and Matrix Computations on Large Message Passing Systems

dc.contributor.authorStewart, G. W.en_US
dc.date.accessioned2004-05-31T22:20:44Z
dc.date.available2004-05-31T22:20:44Z
dc.date.created0000-01en_US
dc.date.issued1998-10-15en_US
dc.description.abstractThis paper is concerned with the consequences for matrix computations of having a rather large number of general purpose processors, say ten or twenty thousand, connected in a network in such a way that a processor can communicate only with its immediate neighbors. Certain communication tasks associated with most matrix algorithms are defined and formulas developed for the time required to perform them under several communication regimes. The results are compared with the times for a nominal $n^3$ floating point operations. The results suggest that it is possible to use a large number of processors to solve matrix problems at a relatively fine granularity, provided fine grain communication is available. Additional figures are available at ftp thales.cs.umd.edu in the directory pub/reports (Also cross-referenced as UMIACS-TR-88-81)en_US
dc.format.extent166851 bytes
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/1903/541
dc.language.isoen_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-2135en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-88-81en_US
dc.titleCommunication and Matrix Computations on Large Message Passing Systemsen_US
dc.typeTechnical Reporten_US

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