Scattering Arrays For Matrix Computations

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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.

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