Abstract
We present fast and highly scalable parallel computations for a number of important and fundamental matrix problems on linear arrays with reconfigurable pipelined optical bus systems. These problems include computing the Nth power, the inverse, the characteristic polynomial, the determinant, the rank, and an LU- and a QR-factorization of a matrix, and solving linear systems of equations. These computations are based on efficient implementation of the fastest sequential matrix multiplication algorithm, and are highly scalable over a wide range of system size. Such fast and scalable parallel matrix computations were not seen before on distributed memory parallel computing systems.
A complete version of the paper is available as Technical Report #00-100, Dept. of Mathematics and Computer Science, SUNY at New Paltz, January 2000. See http://www.mcs.newpaltz.edu/tr.
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© 2000 Springer-Verlag Berlin Heidelberg
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Li, K. (2000). Fast and Scalable Parallel Matrix Computations with Optical Buses. In: Rolim, J. (eds) Parallel and Distributed Processing. IPDPS 2000. Lecture Notes in Computer Science, vol 1800. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45591-4_145
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DOI: https://doi.org/10.1007/3-540-45591-4_145
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