Method of implementing a neural network on a digital computer

Abstract

A digital computer architecture specifically tailored for implementing a neural network. Several simultaneously operable processors (10) each have their own local memory (17) for storing weight and connectivity information corresponding to nodes of the neural network whose output values will be calculated by said processor (10). A global memory (55,56) is coupled to each of the processors (10) via a common data bus (30). Output values corresponding to a first layer of the neural network are broadcast from the global memory (55,56) into each of the processors (10). The processors (10) calculate output values for a set of nodes of the next higher-ordered layer of the neural network. Said newly-calculated output values are broadcast from each processor (10) to the global memory (55,56) and to all the other processors (10), which use the output values as a head start in calculating a new set of output values corresponding to the next layer of the neural network.