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Hypercube Algorithms on the Polymorphic Torus
dc.contributor.author | Elster, Anne C. | en_US |
dc.contributor.author | Li, Hungwen | en_US |
dc.date.accessioned | 2007-04-23T17:36:11Z | |
dc.date.available | 2007-04-23T17:36:11Z | |
dc.date.issued | 1989-05 | en_US |
dc.identifier.citation | http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR89-1003 | en_US |
dc.identifier.uri | https://hdl.handle.net/1813/6803 | |
dc.description.abstract | The Polymorphic Torus architecture is a reconfigurable, massively parallel finegrained system, which in its two-dimensional $(N^{2})$ case has a lower wiring complexity than, say, hypercubes. However, due to the dynamic connection features at run-time, it allows several parallel structures such as trees, rings, and hypercubes to be emulated efficiently. In this paper, we consider algorithms that are especially well-suited for hypercubes, i.e. algorithms that take advantage of the relatively high connectivity of the hypercube topology, and show how these algorithms attain comparable bounds on a 2-D Polymorphic Torus. In particular, algorithms for dense matrix vector multiplication (including using 2 orthogonal trees for the matrix-vector case), sparse matrix-vector multiplication, and the FFT are discussed. | en_US |
dc.format.extent | 1812035 bytes | |
dc.format.extent | 440931 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | application/postscript | |
dc.language.iso | en_US | en_US |
dc.publisher | Cornell University | en_US |
dc.subject | computer science | en_US |
dc.subject | technical report | en_US |
dc.title | Hypercube Algorithms on the Polymorphic Torus | en_US |
dc.type | technical report | en_US |