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

• المؤلفون الرئيسيون: Ni, Leibin, Liu, Zichuan, Yu, Hao, Joshi, Rajiv V.
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2017
• الموضوعات: Approximate computing; Neural network hardware
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/85536; http://hdl.handle.net/10220/43795

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...