在旋转轨道扭矩域壁面设备中模拟神经元和突触功能
Durgesh Kumar1, Ramu Maddu1, Hong Jing Chung2
1School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore, 637371, Singapore. prem@ntu.edu.sg.
Nanoscale horizons
|September 10, 2024
概括
这项研究介绍了新的旋转轨道扭矩域墙壁设备,用于节能的神经形态计算. 研究人员证明了功能神经元和突触,提高了灵敏度和信号噪声比.
科学领域:
- 这就是Spintronics.
- 神经形态计算是一种神经形态计算.
- 材料科学 材料科学 材料科学
背景情况:
- 神经形态计算 (NC) 架构提供了节能计算.
- 旋转轨道扭矩 (SOT) 域壁 (DW) 设备对节能NC有希望.
- 基于DW的神经元和突触的实验研究是有限的.
研究的目的:
- 用新的阅读和写作策略来展示神经元和突触的节能运作.
- 为基于旋转的NC架构开发合成神经元和突触.
- 为了提高DW设备的NC应用的性能.
主要方法:
- 使用基于W/CoFeB的SOT机制进行低电流密度的DW操纵.
- 采用状装置来实现突触功能,导致9个不同的电阻状态.
- 设计了多对异常霍尔条来增强灵敏度和信号噪声比 (SNR).
- 进行了微磁模拟和运输测量.
主要成果:
- 在对突触功能的实验中实现了9种不同的电阻状态.
- 实验证明了功能性的尖峰和步骤神经元.
- 与传统的大厅十字相比,在工程异常的大厅条中提高了灵敏度和SNR.
- 验证了DW神经元和突触的节能运行.
结论:
- 小说阅读和写作策略使得DW神经元和突触的能量效率高.
- 子装置和工程霍尔条显著改善突触和神经元的功能.
- 这项工作推动了基于旋转的神经形态计算架构的发展.
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