由2D铁电半导体晶体管启用的等级处理,用于低功耗和高效的AI视觉系统
Guangcheng Wu1, Li Xiang1, Wenqiang Wang1
1Key Laboratory for Micro-Nano Physics and Technology of Hunan Province, State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Materials Science and Engineering, Hunan University, Changsha 410082, China; Hunan Institute of Optoelectronic Integration, Hunan University, Changsha 410082, China.
Science bulletin
|December 20, 2023
概括
工程师们开发了一种新化晶体管,用于先进的人工光神经和电神经突触. 这一突破使人工智能视觉系统能够高效地进行传感器内处理和内存内计算.
科学领域:
- 材料科学 材料科学 材料科学
- 半导体物理 半导体物理
- 人工智能 硬件 硬件
背景情况:
- 由于分开的传感器,内存和计算单元,传统硬件面临效率和功率限制.
- 越来越多的数据和物联网加剧了这些硬件挑战.
- 需要新的材料和架构来实现集成处理和内存功能.
研究的目的:
- 设计和演示用于人工突触的α相化 (α-In2Se3) 晶体管.
- 为了使处理在传感器 (PIS) 和计算在内存 (CIM) 功能使用二维铁电半导体通道.
- 评估α-In2Se3晶体管在光神经和电神经突触应用中的性能.
主要方法:
- 使用α-In2Se3作为二维铁电半导体通道材料制造晶体管.
- 将晶体管的性能描述为光神经突触,测量光响应性和检测性.
- 评估晶体管作为电神经突触的性能,评估程序/删除速度和能源消耗.
- 将α-In2Se3晶体管集成到AI视觉系统中,以展示PIS和CIM功能.
主要成果:
- α-In2Se3晶体管表现出高光响应度 (2855 A/W) 和检测能力 (2.91 × 10^14 斯) 作为一个光神经突触.
- 作为一个电神经突触,它实现了快速的程序/删除速度 (40 ns/50 μs) 和超低的能耗 (0.37 aJ/spike).
- 利用这些晶体管的AI视觉系统在12个时代内实现了92.63%的识别精度,展示了协同作用的PIS和CIM效应.
结论:
- α-In2Se3晶体管显示出下一代视觉硬件的巨大潜力.
- 开发的设备提高了人工智能应用中的处理效率和功率效率.
- 这项工作为先进的集成传感和计算系统铺平了道路.
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