Trends and challenges in the circuit and macro of RRAM-based computing-in-memory systems
作者机构：School of Integrated Circuits(SIC)Tsinghua UniversityBeijingChina Beijing Innovation Center for Future Chips(ICFC)Tsinghua UniversityBeijingChina
出 版 物：《Chip》 (芯片（英文）)
年 卷 期：2022年第1卷第1期
页 面：19-29页
核心收录：
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by the China key research and develop-ment program(2019YFB2205403)
主 题：RRAM computing artificial
摘 要：Conventional von Neumann architecture faces many challenges in dealing with data-intensive artificial intelligence tasks efficiently due to huge amounts of data movement between physically separated data computing and storage *** computing-in-memory(CIM)ar-chitecture implements data processing and storage in the same place,and thus can be much more energy-efficient than state-of-the-art von Neumann *** with their counterparts,resis-tive random-access memory(RRAM)-based CIM systems could consume much less power and area when processing the same amount of *** this paper,we first introduce the principles and challenges re-lated to RRAM-based CIM ***,recent works on the circuit and macro levels of RRAM-CIM systems will be reviewed to highlight the trends and challenges in this field.
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