Litcius/Paper detail

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS<sub>2</sub>

Guilherme Migliato Marega, Zhenyu Wang, Maksym Paliy, Gino Giusi, Sebastiano Strangio, Francesco Castiglione, Christian Callegari, Mukesh Tripathi, Aleksandra Rađenović, Giuseppe Iannaccone, András Kis

2022ACS Nano43 citationsDOIOpen Access PDF

Abstract

and transferred from a host. Further simulations project that at a system level, the large memory arrays can perform AlexNet classification with an upper limit of 50 000 TOpS/W, potentially outperforming neural network integrated circuits based on double-poly CMOS technology.

Topics & Concepts

Computer scienceArtificial neural networkVon Neumann architecturePerceptronCMOSResistive random-access memoryNeuromorphic engineeringFlash memoryMemristorElectronic circuitComputer hardwareDeep learningArtificial intelligenceElectronic engineeringElectrical engineeringMaterials scienceVoltageOptoelectronicsEngineeringOperating systemAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeural Networks and Reservoir Computing