An Artificial Neutral Network Chip Based on Two-Dimensional Semiconductor

Abstract

Two-dimensional semiconductors can be used to build integrated circuits for running artificial neural networks (ANN) with higher energy efficiency. The implementation of an ANN with 2D semiconductors has been held back by the large-scale and high-quality transistors required for running machine learning algorithms. Here we demonstrate the first functional MoS2 analog ANN integrated circuit, including memory, multiply-and-accumulate (MAC), activation function, and weight update circuits. The ANN integrated circuit is realized through 818 field effect transistors (FETs) with wafer-scale and high-homogeneity MoS2 film. The large current on/off ratio and output linearity of these MoS2 FETs allow the realization of convolutional and activation function circuits with a few number of transistors. This ANN can be used for recognizing tactile digit, showing the recognition rate exceeding 97%. Our work demonstrates wafer-scale processing of a 2D semiconductor for building integrated circuits with the functions of AI computation.