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
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