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A Stream Algorithm for the SVD

dc.date.accessioned2005-12-22T01:09:48Z
dc.date.accessioned2018-11-24T10:23:56Z
dc.date.available2005-12-22T01:09:48Z
dc.date.available2018-11-24T10:23:56Z
dc.date.issued2003-10-22
dc.identifier.urihttp://hdl.handle.net/1721.1/30429
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/30429
dc.description.abstractWe present a stream algorithm for the Singular-Value Decomposition (SVD) of anM X N matrix A. Our algorithm trades speed of numerical convergence for parallelism,and derives from a one-sided, cyclic-by-rows Hestenes SVD. Experimental results showthat we can create O(M) parallelism, at the expense of increasing the computationalwork by less than a factor of about 2. Our algorithm qualifes as a stream algorithmin that it requires no more than a small, bounded amount of local storage per processor and its compute efficiency approaches an optimal 100% asymptotically for largenumbers of processors and appropriate problem sizes.
dc.format.extent31 p.
dc.format.extent30567456 bytes
dc.format.extent1124918 bytes
dc.language.isoen_US
dc.titleA Stream Algorithm for the SVD


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