A Systolic Architecture for the Singular Value Decomposition

A systolic architecture for computing a singular value decomposition of an m x n matrix, where m \geq n, is proposed, which is stable and requires only $O(mn)$ time on a linear array of O(n) processors.

Abstract

We propose a systolic architecture for computing a singular value decomposition of an m x n matrix, where $m \\geq n$. Our algorithm is stable and requires only $O(mn)$ time on a linear array of $O(n)$ processors. Extensions to algorithms for two-dimensional arrays are also discussed. Key Words and Phrases: Systolic arrays, singular value decomposition, Hestenes method, threshold Jacobi method, real-time computation.