Self‐Rectifying Memristors for Three‐Dimensional In‐Memory Computing
Source abstract
Abstract
Abstract 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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Photoreceptor and optogenetics research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Integrated Circuits Hubei Key Laboratory of Advanced Memories Huazhong University of Science and Technology Wuhan 430074 China
Hubei Yangtze Memory Laboratories Wuhan 430205 China
Funding
National Natural Science Foundation of China
References (100+)
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