An Energy-Efficient Digital ReRAM-Crossbar-Based CNN With Bitwise Parallelism

• Main Authors: Ni, Leibin, Liu, Zichuan, Yu, Hao, Joshi, Rajiv V.
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2017
• Subjects: Approximate computing; Neural network hardware
• Online Access: https://hdl.handle.net/10356/85536; http://hdl.handle.net/10220/43795
• Institution: Nanyang Technological University

There is great attention to develop hardware accelerator with better energy efficiency, as well as throughput, than GPUs for convolutional neural network (CNN). The existing solutions have relatively limited parallelism as well as large power consumption (including leakage power). In this paper, we...