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Self-Rectifying Memristors for Three-Dimensional In-Memory Computing
DOI:10.1002/adma.202307218.png)
摘要
En 中文
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 (>10(2) 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.
Keyword:
resistive switching
self-rectifying memristor
3D integration
in-memory computing
neuromorphic computing
期刊
IF:
26.8
论文数:
3.4W
被引数:
46.0W
机构
暂无机构信息
引用论文
Memristor crossbar arrays with 6-nm half-pitch and 2-nm critical dimension
NATURE NANOTECHNOLOGY
IF34.9
Multilayer Reservoir Computing Based on Ferroelectric α-In2Se3 for Hierarchical Information Processing基于铁电 α-In2Se3的多层储层计算,用于分层信息处理
ADVANCED MATERIALS
IF26.8
Low-Power, Self-Rectifying, and Forming-Free Memristor with an Asymmetric Programing Voltage for a High-Density Crossbar Application具有非对称编程电压的低功耗,自整流和无成形忆阻器,用于高密度交叉开关应用
NANO LETTERS
IF9.1

