Neural network based on total hamming distance

Abstract

Disclosed herein includes a system, a method, and a device for improving power efficiency of a neural network implemented in an AI chip. In a neural network, large amounts of computations for multiply and accumulate can result in frequent toggles or transitions in states of logic circuits in the AI chip. Such frequent toggles or transitions of states of logic circuits can cause a large overall power consumption. In one aspect, to minimize the number of toggles, a sequence or order of computations can be rearranged. In one approach, total hamming distances for weights or input strings in different arrangements or sequences can be identified, and an arrangement or a sequence of weights or input strings with a reduced or minimum total hamming distance can be identified. An arrangement or a sequence of weights that render a reduced total hamming distance can be identified.