Litcius/Paper detail

2D materials–based homogeneous transistor-memory architecture for neuromorphic hardware

Lei Tong, Zhuiri Peng, Runfeng Lin, Zheng Li, Yilun Wang, Xinyu Huang, Kan‐Hao Xue, Hangyu Xu, Feng Liu, Hui Xia, Peng Wang, Mingsheng Xu, Wei Xiong, Weida Hu, Jianbin Xu, Xinliang Zhang, Lei Ye, Xiangshui Miao

2021Science325 citationsDOI

Abstract

In neuromorphic hardware, peripheral circuits and memories based on heterogeneous devices are generally physically separated. Thus, exploration of homogeneous devices for these components is key for improving module integration and resistance matching. Inspired by the ferroelectric proximity effect on two-dimensional (2D) materials, we present a tungsten diselenide–on–lithium niobate cascaded architecture as a basic device that functions as a nonlinear transistor, assisting the design of operational amplifiers for analog signal processing (ASP). This device also functions as a nonvolatile memory cell, achieving memory operating (MO) functionality. On the basis of this homogeneous architecture, we also investigated an ASP-MO integrated system for binary classification and the design of ternary content-addressable memory for potential use in neuromorphic hardware.

Topics & Concepts

Neuromorphic engineeringHomogeneousComputer architectureComputer scienceTransistorArchitectureComputer hardwareParallel computingArtificial neural networkArtificial intelligencePhysicsEngineeringElectrical engineeringThermodynamicsVoltageVisual artsArtAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeuroscience and Neural Engineering