基于Zr-Doped HfO2Memcapacitive Synapse Arrays的高功率多感应储水器计算
Mengjiao Pei1, Ying Zhu1, Siyao Liu1
1National Laboratory of Solid-State Microstructures, School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, P. R. China.
Advanced materials (Deerfield Beach, Fla.)
|August 12, 2023
概括
研究人员开发了一种基于氧化物的新型memcapacitive突触,用于高效的储库计算. 这项技术能够在超低功耗的情况下实现强大的时间处理,优于现有的电阻方法.
科学领域:
- 材料科学 材料科学 材料科学
- 神经形态工程的神经形态工程
- 计算机科学 计算机科学
背景情况:
- 储计算需要高效的硬件进行时间处理.
- 容量储提供了潜在的功率效率,但仍未得到充分探索.
- 现有的电阻记忆器在功耗和性能方面存在局限性.
研究的目的:
- 开发一种基于氧化物的功率高效的memcapacitive synapse (OMC) 用于储库计算.
- 调查Zr-doped HfO2 (HZO) 在容量储应用中的潜力.
- 展示一个具有高精度和低功耗的多传感器处理系统.
主要方法:
- 制造Zr-doped HfO2 (HZO) 的电容器件.
- 装置非线性和状态丰富性用于储库计算的表征.
- 在基准任务上实施和测试基于OMC的水库计算系统.
- 展示用于虚拟购物的无触摸用户界面.
主要成果:
- OMC 设备表现出非线性和状态丰富性,适合储计算.
- 实现了超低功耗 (≈113.4 fJ 每个尖峰),性能优于电阻储存器.
- 在识别声学,电生理学和机械数据方面表现出高精度 (>94%) .
- 成功实现了一个概念验证的无触摸用户界面.
结论:
- Zr-doped HfO2 memcapacitive 突触对于高功率的储计算是有效的.
- 开发的系统提供了卓越的时间处理和多感官识别能力.
- 这项工作为先进的低功耗人机接口和机器学习平台铺平了道路.
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