神经形态工程学
计算机科学
冯·诺依曼建筑
计算机体系结构
高效能源利用
油藏计算
带宽(计算)
光子学
钥匙(锁)
非常规计算
光学计算
记忆电阻器
电子工程
人工智能
光电子学
材料科学
人工神经网络
分布式计算
工程类
电气工程
电信
循环神经网络
操作系统
计算机安全
作者
Seungho Song,Jeehoon Kim,Sung Min Kwon,Jeong‐Wan Jo,Sung Kyu Park,Yong‐Hoon Kim
标识
DOI:10.1002/aisy.202000119
摘要
Conventional von Neumann–based computing systems have inherent limitations such as high hardware complexity, relatively inferior energy efficiency, and low bandwidth. As an alternative, neuromorphic computation is emerging as a platform for next‐generation artificial intelligence computing systems due to their potential advantages such as highly energy‐efficient computing, robust learning, fault tolerance, and parallel processing. Moreover, to further enhance the energy efficiency and processing speed, photonic‐based neuromorphic systems have gathered significant interest in the past few years. Herein, the recent progress and development of optoelectronic and all‐optical neuromorphic devices is summarized, focusing on their structures, materials, and potential applications. Particularly, for optoelectronic neuromorphic devices, devices with planar and vertical structures are described along with their key strategies in materials and device structures. Next, all‐optical memory and neuromorphic devices for neuromorphic computing are reviewed. Finally, the applications of optoelectronic neuromorphic devices are discussed for their potential utilization in neuromorphic computing systems.
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