标准晶体管中的突触和神经行为
Sebastian Pazos1, Kaichen Zhu1, Marco A Villena1
1Materials Science and Engineering, Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
Nature
|March 27, 2025
概括
研究人员开发了一种新的2晶体管细胞,模仿神经和突触功能,显著降低了人工神经网络 (ANN) 的复杂性. 这一突破为使用标准CMOS技术构建先进的人工智能硬件提供了更节能的方法.
科学领域:
- 电子产品
- 计算机科学
- 材料科学
背景情况:
- 人工神经网络 (ANN) 越来越多地用于节能计算的硬件.
- 目前的神经形态计算机使用复杂的电路,每个神经元和突触都有许多晶体管.
- 简化这些构建块对于开发更先进和更有效的ANN至关重要.
研究的目的:
- 证明单个互补的金属氧化物半导体 (CMOS) 晶体管可以表现出神经和突触行为.
- 使用最小的晶体管开发一种简化,多功能的神经突触随机访问记忆 (NS-RAM) 细胞.
- 探索更复杂,更大,更节能的ANN的潜力.
主要方法:
- 以一种非常规的方式偏离单个CMOS晶体管以诱导神经和突触功能.
- 连接两个CMOS晶体管以创建一个多功能的2晶体管NS-RAM电池.
- 使用成熟的CMOS平台来制造高产量,低变量的设备.
主要成果:
- 一个CMOS晶体管显示可调节的神经和突触特征.
- 开发的2晶体管NS-RAM细胞表现出可调节的神经突触反应.
- 制造过程实现了100%的产量和设备间极低的可变性.
结论:
- 一个简化的2晶体管细胞可以有效地模拟神经和突触功能,减少硬件复杂性.
- 这种方法利用现有的CMOS技术实现高效的人工智能硬件.
- 该NS-RAM电池为下一代节能ANN提供了一个有前途的途径.
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