作者
Geng Yuan, Xiaolong Ma, Caiwen Ding, Sheng Lin, Tianyun Zhang, Zeinab S Jalali, Yilong Zhao, Li Jiang, Sucheta Soundarajan, Yanzhi Wang
发表日期
2019/7/29
研讨会论文
(ISLPED) 2019 IEEE/ACM International Symposium on Low Power Electronics and Design
页码范围
1-6
出版商
IEEE
简介
The high computation and memory storage of large deep neural networks (DNNs) models pose intensive challenges to the conventional Von-Neumann architecture, incurring sub-stantial data movements in the memory hierarchy. The memristor crossbar array has emerged as a promising solution to mitigate the challenges and enable low-power acceleration of DNNs. Memristor-based weight pruning and weight quantization have been seperately investigated and proven effectiveness in reducing area and power consumption compared to the original DNN model. However, there has been no systematic investigation of memristor-based neuromorphic computing (NC) systems considering both weight pruning and weight quantization. In this paper, we propose an unified and systematic memristor-based framework considering both structured weight pruning and weight quantization by incorporating alternating …
学术搜索中的文章
G Yuan, X Ma, C Ding, S Lin, T Zhang, ZS Jalali… - 2019 IEEE/ACM International Symposium on Low …, 2019