一种具有短期记忆力的低功耗垂直双门神经传感器,用于高能效的神经形态计算
Han Xu1,2,3,4, Dashan Shang5,6,7, Qing Luo1,2,3
1State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China.
Nature communications
|October 11, 2023
概括
研究人员开发了一种用于树突计算的新型神经递质,实现了类似大脑的能量效率. 这种紧的低功耗设备能够实现先进的神经形态计算应用,为高效的人工智能铺平道路.
科学领域:
- 神经科学和计算机工程 神经科学和计算机工程
- 人工智能和神经形态系统
背景情况:
- 神经形态计算试图利用电子系统模仿大脑功能.
- 灵感来自于生物神经元的树突计算,增强了人工神经网络的能力.
- 目前的人工树突很难与大脑的能效和吞吐量相匹配.
研究的目的:
- 开发一个紧的,低功率的神经传感器,用于高效的树突计算.
- 使用新型设备演示先进的类似大脑的计算功能.
- 探索神经晶体管在下一代神经形态系统中的潜力.
主要方法:
- 一个垂直的双门电解质通道晶体管 (EGT) 的制造,通道长度为30nm.
- 神经传感器的短期记忆和低功耗性能 (~3.16 fW读取功率,~30 fJ读取能量) 的表征.
- 演示了树突集成,数字/模拟树突计算用于巧合检测,以及硬件神经网络用于声音定位.
主要成果:
- 在神经递质器中实现了创纪录的低读取功率和生物学可比的读取能量.
- 通过使用该设备成功证明了树集成和巧合检测.
- 开发了一个硬件神经网络,展示了生物灵感的声音定位能力.
结论:
- 开发的神经传感器为节能的人工树突提供了一个有前途的途径.
- 这项技术可以使下一代的神经形态计算具有大脑水平的效率.
- 基于神经传递器的方法可以实现先进的,类似大脑的计算功能.
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