基于硬件的3D单立体集成神经系统,具有挥发性和非挥发性设备的增强记忆窗口
Yu-Rim Jeon1, Donguk Seo2, Yoonmyung Lee2
1Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas, 78172, USA.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|June 17, 2024
概括
这项研究展示了一个3D神经形态硬件系统,通过材料和界面工程克服了突触设备中的内存窗口退化. 改进后的系统在图像识别任务中实现了高精度.
科学领域:
- 材料科学 材料科学 材料科学
- 神经科学是一个神经科学.
- 电气工程 电气工程
背景情况:
- 3D神经形态硬件系统对于先进的AI应用至关重要.
- 晶圆粘合和3D集成可以降低因工艺缺陷和热应力而导致突触设备内存窗口.
研究的目的:
- 为了解决3D集成神经形态设备中的记忆窗口退化问题.
- 为了提高基于硬件的神经系统的突触设备性能.
主要方法:
- 在Ta2O5和HfO2中研究了挥发性memristors的Ag扩散.
- 研究了相互连接和门金属 (Ru),以减少非易失性存储器件中的接口陷.
- 集成的12x14阵列设备与使用晶圆粘合的CMOS电路.
主要成果:
- 在挥发性和非挥发性设备中实现了超过10^6的内存窗口改进.
- 使用训练有素的阵列设备,证明了字母的可识别图像识别,准确率为92%.
- 在3D集成阵列设备中验证了突触特征和重量变化.
结论:
- 在一个集成的3D神经形态硬件系统中,成功调制了高达10^6的内存窗口.
- 拟议的方法减轻了设备的退化,从而实现了强大的神经形态应用.
- 该研究强调了3D集成对先进,高性能神经系统的潜力.
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