| dc.contributor.author | Strumpen, Volker | |
| dc.contributor.author | Hoffmann, Henry | |
| dc.contributor.author | Agarwal, Anant | |
| dc.contributor.other | Computer Architecture | |
| dc.date.accessioned | 2005-12-22T01:09:48Z | |
| dc.date.available | 2005-12-22T01:09:48Z | |
| dc.date.issued | 2003-10-22 | |
| dc.identifier.other | MIT-CSAIL-TR-2003-024 | |
| dc.identifier.other | MIT-LCS-TM-641 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/30429 | |
| dc.description.abstract | We 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.extent | 31 p. | |
| dc.format.extent | 30567456 bytes | |
| dc.format.extent | 1124918 bytes | |
| dc.format.mimetype | application/postscript | |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en_US | |
| dc.relation.ispartofseries | Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory | |
| dc.title | A Stream Algorithm for the SVD | |
