延迟(音频)
计算机科学
电阻式触摸屏
电阻随机存取存储器
神经形态工程学
集合(抽象数据类型)
高效能源利用
染色质结构重塑复合物
氧气
CMOS芯片
扩散
光电子学
材料科学
人工神经网络
电气工程
化学
电极
人工智能
电信
工程类
物理
物理化学
生物化学
基因
有机化学
计算机视觉
热力学
核小体
程序设计语言
组蛋白
作者
Youngjae Kwon,Won-Tae Koo,Sangsu Park,Dong Ik Suh,Gunhee Lee,Hyung Dong Lee,Youngbae Ahn,Dohee Kim,Seung‐Wook Ryu,Hoseok Em,Seokjoon Kang,Chang‐Won Jeong,Jun-Ho Cheon,Hyejung Choi,Soo Gil Kim,Seho Lee,Jaeyun Yi,Seon Yong
标识
DOI:10.1109/imw59701.2024.10536974
摘要
Non-volatile memory-based analog computation-in-memory can improve energy efficiency and latency of artificial intelligence edge devices by minimizing the movement of data between processors and memories. Here, we developed reliable HfO 2 -based resistive synaptic cell (RSC) arrays with 16-level analog properties. We revealed that oxygen diffusion barriers not only suppress the negative-set phenomenon and but also improve retention properties. In addition, we fully integrated 256Kcell 1T1R cross-bar RSC arrays using a conventional CMOS process, and demonstrated their improved multiply–accumulate operations with ~94% accuracy.
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