A highly-parallel and energy-efficient 3D multi-layer CMOS-RRAM accelerator for tensorized neural network

• Main Authors: Huang, Hantao, Ni, Leibin, Wang, Kanwen, Wang, Yuangang, Yu, Hao
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2018
• Subjects: Tensorized Neural Network (TNN); RRAM Computing
• Online Access: https://hdl.handle.net/10356/87049; http://hdl.handle.net/10220/45222
• Institution: Nanyang Technological University

It is a grand challenge to develop highly parallel yet energy-efficient machine learning hardware accelerator. This paper introduces a three-dimensional (3-D) multilayer CMOSRRAM accelerator for atensorized neural network. Highly parallel matrix-vector multiplication can be performed with low power...