神经形态工程学
冯·诺依曼建筑
记忆电阻器
计算机科学
计算机体系结构
萤石
非常规计算
认知计算
铁电性
纳米技术
材料科学
人工神经网络
人工智能
电子工程
分布式计算
光电子学
工程类
神经科学
操作系统
认知
心理学
电介质
冶金
作者
Dong Hyun Lee,Geun Hyeong Park,Se Hyun Kim,Ju Yong Park,Kun Yang,Stefan Slesazeck,Thomas Mikolajick,Min Hyuk Park
出处
期刊:InfoMat
[Wiley]
日期:2022-10-13
卷期号:4 (12)
被引量:48
摘要
Abstract A continuous exponential rise has been observed in the storage and processing of the data that may not curtail in the foreseeable future. The required data processing speed and power consumption are restricted by the buses between the logic and memory devices that are characteristic of the von Neumann computing architecture. Bio‐mimicking neuromorphic computing has garnered considerable academic and industrial interest to resolve these challenges. Additionally, devices based on emerging nonvolatile memories capable of mimicking the behaviors of synapses and neurons, which are the main elements in biological computing systems (brains), are attracting significant interest from the device community. With the discovery of ferroelectricity in fluorite‐structured oxides, such as HfO 2 and ZrO 2 , which are compatible with the state‐of‐the‐art complementary‐metal‐oxide‐semiconductor processes, ferroelectric devices have rapidly evolved as the main direction of these research and development activities. Fundamental science related to fluorite‐structured ferroelectrics has been intensively studied over the last decade. At present, the focus is gradually moving to practical applications, including neuromorphic computing and advanced classical processing or memory units in the conventional von Neumann architecture. However, despite its rapid development, the wealth of recent progress in neuromorphic computing devices based on fluorite‐structured ferroelectrics has not been reviewed and systemized. This progress report comprehensively reviews and systemizes the recent progress in artificial synaptic and spiking neuron devices for neuromorphic computing based on fluorite‐structured ferroelectrics. image
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