Scattering Arrays For Matrix Computations

Jean-Marc Delosme; Martin Morf

doi:10.1117/12.932514

30 July 1982 Scattering Arrays For Matrix Computations

Jean-Marc Delosme, Martin Morf

Proceedings Volume 0298, Real-Time Signal Processing IV; (1982) https://doi.org/10.1117/12.932514
Event: 25th Annual Technical Symposium, 1981, San Diego, United States

Abstract

Several new mesh connected multiprocessor architectures are presented that are adapted to execute highly parallel algorithms for matrix alge-bra and signal processing, such as triangular- and eigen-decomposition, inversion and low-rank updat-ing of general matrices, as well as Toeplitz and Hankel related matrices. These algorithms are based on scattering theory concepts and informa-tion preserving transformations, hence they exhibit local communication, and simple control and memory management, all properties that are ideal for VLSI implementation. The architectures are based on two- dimensional "scattering" arrays, that can be folded into linear arrays, either through time-sharing, or due to simple computation wave-fronts, or due to special structures of the matrices involved, such as Toeplitz.

Citation Download Citation

Jean-Marc Delosme and Martin Morf "Scattering Arrays For Matrix Computations", Proc. SPIE 0298, Real-Time Signal Processing IV, (30 July 1982); https://doi.org/10.1117/12.932514

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