A review on SRAM-based computing in-memory:Circuits,functions,and applications

• 作者: Zhiting Lin Zhongzhen Tong Jin Zhang Fangming Wang Tian Xu Yue Zhao Xiulong Wu Chunyu Peng Wenjuan Lu Qiang Zhao Junning Chen
• 来源期刊: 半导体学报（英文版）
• 年，卷（期）: 2022,（3）
• 所属期刊栏目: REVIEWS
• 页码范围: 19-43
• 页数: 25页
• 语种: 英文
• DOI: 10.1088/1674-4926/43/3/031401

摘要

Artificial intelligence(AI)processes data-centric applications with minimal effort.However,it poses new challenges to system design in terms of computational speed and energy efficiency.The traditional von Neumann architecture cannot meet the requirements of heavily data-centric applications due to the separation of computation and storage.The emergence of computing in-memory(CIM)is significant in circumventing the von Neumann bottleneck.A commercialized memory architec-ture,static random-access memory(SRAM),is fast and robust,consumes less power,and is compatible with state-of-the-art tech-nology.This study investigates the research progress of SRAM-based CIM technology in three levels:circuit,function,and applic-ation.It also outlines the problems,challenges,and prospects of SRAM-based CIM macros.