铁电定义的可重新配置的同型连接器用于内存传感和计算
Guangjian Wu1,2,3, Xumeng Zhang1,2,3, Guangdi Feng4
1State Key Laboratory of Integrated Chips and Systems, Frontier Institute of Chip and System, Fudan University, Shanghai, China.
Nature materials
|September 28, 2023
概括
本研究介绍了使用铁电光二极管阵列的集成内存传感和计算架构. 这种新的设计可实现高效的图像识别,低能耗和延迟,消除了对外部内存和计算单元的需求.
科学领域:
- 材料科学 材料科学 材料科学
- 计算机工程 计算机工程
- 电气工程 电气工程
背景情况:
- 对以数据为中心的应用程序的需求日益增长,需要在延迟和能源严格的环境中进行高效的处理.
- 现有的内存和内传感器计算方法在将整个信号链集成到单个设备中面临挑战.
研究的目的:
- 展示一种新的内存传感和计算架构,集成传感,内存和计算.
- 在传感硬件中直接实现高水平的认知计算.
主要方法:
- 使用了铁电定义的可重新配置的二维光二极管阵列.
- 杆光电流生成和基尔霍夫定律用于计算乘法.
- 采用铁电领域进行局部重量存储和编程,达到5比特以上的精度.
主要成果:
- 成功展示了一个集成架构,在没有外部内存或计算单元的情况下执行图像识别.
- 使用铁电领域实现了51个可区分的重量状态,具有线性,对称和可逆操纵.
- 该系统集成了高级计算,重量记忆和高性能传感.
结论:
- 开发的三合一模式提供了一个有前途的计算架构,显著降低了能源消耗,延迟和硬件开销.
- 这种方法为下一代边缘计算设备和数据中心应用程序铺平了道路.
- 基于铁电的内存传感和计算代表了硬件效率的重大进步.
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