Self‐Rectifying Memristors for Three‐Dimensional In‐Memory Computing

Costly data movement in terms of time and energy in traditional von Neumann systems is exacerbated by emerging information technologies related to artificial intelligence. In‐memory computing (IMC) architecture aims to address this problem. Although the IMC hardware prototype represented by a memris...

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Vydané v:Advanced materials (Weinheim) Ročník 36; číslo 4; s. e2307218 - n/a
Hlavní autori: Ren, Sheng‐Guang, Dong, A‐Wei, Yang, Ling, Xue, Yi‐Bai, Li, Jian‐Cong, Yu, Yin‐Jie, Zhou, Hou‐Ji, Zuo, Wen‐Bin, Li, Yi, Cheng, Wei‐Ming, Miao, Xiang‐Shui
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Germany Wiley Subscription Services, Inc 01.01.2024
Predmet:
3D integration
Artificial intelligence
Computer memory
Density
Hardware
in‐memory computing
Memristors
neuromorphic computing
Power consumption
resistive switching
self‐rectifying memristor
3D integration
resistive switching
in-memory computing
self-rectifying memristor
neuromorphic computing
ISSN:0935-9648, 1521-4095, 1521-4095
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Popis
Shrnutí:Costly data movement in terms of time and energy in traditional von Neumann systems is exacerbated by emerging information technologies related to artificial intelligence. In‐memory computing (IMC) architecture aims to address this problem. Although the IMC hardware prototype represented by a memristor is developed rapidly and performs well, the sneak path issue is a critical and unavoidable challenge prevalent in large‐scale and high‐density crossbar arrays, particularly in three‐dimensional (3D) integration. As a perfect solution to the sneak‐path issue, a self‐rectifying memristor (SRM) is proposed for 3D integration because of its superior integration density. To date, SRMs have performed well in terms of power consumption (aJ level) and scalability (>102 Mbit). Moreover, SRM‐configured 3D integration is considered an ideal hardware platform for 3D IMC. This review focuses on the progress in SRMs and their applications in 3D memory, IMC, neuromorphic computing, and hardware security. The advantages, disadvantages, and optimization strategies of SRMs in diverse application scenarios are illustrated. Challenges posed by physical mechanisms, fabrication processes, and peripheral circuits, as well as potential solutions at the device and system levels, are also discussed. This review summarizes the research progress in self‐rectifying memristors (SRM) and SRM‐based applications including 3D memory, in‐memory computing, neuromorphic computing, and hardware security. Through a comprehensive analysis of the advantages and disadvantages of SRMs in different application scenarios, as well as challenges at the device, 3D integration, and peripheral circuit levels, corresponding research ideas and potential solutions are proposed.
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ISSN:0935-9648
1521-4095
1521-4095
DOI:10.1002/adma.202307218