记忆电阻器
神经形态工程学
材料科学
冯·诺依曼建筑
瓶颈
计算机科学
纳米技术
带宽(计算)
集成电路
光电子学
电子工程
计算机体系结构
电信
工程类
人工神经网络
嵌入式系统
人工智能
操作系统
作者
Jinyong Wang,Nasir Ilyas,Yujing Ren,Yun Ji,Sifan Li,Changcun Li,Fucai Liu,Deen Gu,Kah‐Wee Ang
标识
DOI:10.1002/adma.202307393
摘要
Optoelectronic memristors (OMs) have emerged as a promising optoelectronic Neuromorphic computing paradigm, opening up new opportunities for neurosynaptic devices and optoelectronic systems. These OMs possess a range of desirable features including minimal crosstalk, high bandwidth, low power consumption, zero latency, and the ability to replicate crucial neurological functions such as vision and optical memory. By incorporating large-scale parallel synaptic structures, OMs are anticipated to greatly enhance high-performance and low-power in-memory computing, effectively overcoming the limitations of the von Neumann bottleneck. However, progress in this field necessitates a comprehensive understanding of suitable structures and techniques for integrating low-dimensional materials into optoelectronic integrated circuit platforms. This review aims to offer a comprehensive overview of the fundamental performance, mechanisms, design of structures, applications, and integration roadmap of optoelectronic synaptic memristors. By establishing connections between materials, multilayer optoelectronic memristor units, and monolithic optoelectronic integrated circuits, this review seeks to provide insights into emerging technologies and future prospects that are expected to drive innovation and widespread adoption in the near future.
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