Multiply-accumulate calculation method and circuit suitable for neural network

Abstract

The present invention relates to the field of analog integrated circuits, and provides a multiply-accumulate calculation method and circuit suitable for a neural network, which realizes large-scale multiply-accumulate calculation of the neural network with low power consumption and high speed. The multiply-accumulate calculation circuit comprises a multiplication calculation circuit array and an accumulation calculation circuit. The multiplication calculation circuit array is composed of M groups of multiplication calculation circuits. Each group of multiplication calculation circuits is composed of one multiplication array unit and eight selection-shift units. The order of the multiplication array unit is quantized in real time by using on-chip training to provide a shared input for the selection-shift units, achieving increased operating rate and reduced power consumption. The accumulation calculation circuit is composed of a delay accumulation circuit, a TDC conversion circuit, and a shift-addition circuit in series. The delay accumulation circuit comprises eight controllable delay chains for dynamically controlling the number of iterations and accumulating data multiple times in a time domain, so as to meet the difference in calculation scale of different network layers, save hardware storage space, reduce calculation complexity, and reduce data scheduling.