电子学报2024，Vol.52Issue(4)：1103-1117,15.DOI:10.12263/DZXB.20230967
存算一体技术研究现状
Research Status of Computing-in-Memory Technology
摘要
Abstract
Von Neumann computer architecture faces the bottleneck of"storage wall",which hindering the performance improvement of AI(Artificial Intelligence)computing.Computing-In-Memory(CIM)breaks the limitation of"storage wall"and greatly improves the performance of AI computing.At present,CIM schemes have been implemented in a variety of storage media.According to the type of calculation signal,CIM scheme can be divided into digital CIM and analog CIM scheme.CIM has greatly improved the performance of AI computing,but the further development still faces major challenges.This article provides a detailed comparative analysis of CIM schemes in different signal domains,pointing out the main advantages and disadvantages of each scheme,and also pointing out the challenges faced by CIM.We believe that with the cross level col-laborative research and development of process integration,devices,circuits,architecture,and software toolchains,CIM will provide more powerful and efficient computing power for AI computing at the edge and cloud ends.关键词
人工智能/存算一体/存储介质/计算信号类型/评价指标Key words
artificial intelligence/computing-in-memory/storage media/calculate signal type/evaluation index分类
信息技术与安全科学引用本文复制引用
李嘉宁,姚鹏,揭路,唐建石,伍冬,高滨,钱鹤,吴华强..存算一体技术研究现状[J].电子学报,2024,52(4):1103-1117,15.基金项目
国家自然科学基金(No.92164302,No.62025111) National Natural Science Foundation of China(No.92164302,No.62025111) （No.92164302,No.62025111）
