Scalable parallel group partitioned diagonal-fold switching tree

Abstract

A parallel computer architecture supporting neural networks utilizing a novel method of separating a triangular array containing N processing elements on each edge into multiple smaller triangular arrays, each of dimension X and each representing a common building block processor group chip that can be interconnected for various size parallel processing implementations. The group chips are interconnected by a unique switching tree mechanism that maintains the complete connectivity capability and functionality possessed by the original triangular array of dimension N. For a given size K and X, K divisible by X, a triangular array containing K processor elements located on each edge of an equilateral triangular array is partitioned into K/X triangular arrays of dimension X and K(K-X)/2X.sup.2 square processor arrays of dimension X. An algorithm partitions a square array into two triangular arrays, each of dimension X. Assuming K=N and the chosen technology supports the placement of a triangular processor group chip of dimension X on a single chip, the final scalable parallel computing structure for N root tree processors utilizes N.sup.2 /X.sup.2 triangular processor group chips. The partitioning methodology creates a scalable organization of processor elements. An interconnection mechanism preserves the functionality of the original triangular array of dimension N in the implemented structure constructed of multiple triangular arrays of dimension X.