童浩

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Personal information

教授     博士生导师    

所在单位:集成电路学院

学历:研究生(博士)毕业

学位:博士学位

毕业院校:华中科技大学

学科:微电子学与固体电子学
曾获荣誉:
2024    华中科技大学青年五四奖章
2022    华为奥林帕斯先锋奖
2020    湖北省技术发明一等奖(排名第2)
2013    湖北省年度“十大科技事件”
2013    湖北省优秀博士学位论文
2014    湖北省优秀学士学位论文指导教师
2015    华中科技大学教师教学竞赛二等奖
2017    华中科技大学光学与电子信息学院“我最喜爱的教师班主任“
2020    华中科技大学光学与电子信息学院突出贡献一等奖

Resistance Drift-Reduced Multilevel Storage and Neural Network Computing in Chalcogenide Phase Change Memories by Bipolar Operation
发布时间:2023-08-21  点击次数:

论文类型:期刊论文
第一作者:李鑫
通讯作者:何强,童浩
合写作者:何强,童浩
发表刊物:IEEE Electron Device Letters
所属单位:华中科技大学
学科门类:工学
一级学科:电子科学与技术
文献类型:J
卷号:43
期号:4
页面范围:565-568
关键字:相变存储器、双极性操作、阻值漂移、电导水平、、神经网络、卷积神经网络
DOI码:10.1109/LED.2022.3154440
发表时间:4461-06-01
摘要:Phase change materials, which has been focused on the non-volatile memory field, show the possibility to carry out data storage and computing in the same physical location. However, the resistance drift behavior of phase change memory has been a huge barrier not only to traditional binary memory application for a long time, but to multi-level storage and therefore the neural network computing. Here, a bipolar programming scheme is exploited to achieve drift-reduced intermediate states and convolutional neural network (CNN) computations in Ge 2 Sb 2 Te 5 (GST) based memory cells. Experiments show that the resistance drift phenomena under bipolar programming have been reduced. Furthermore, the impact of bipolar operation on CNN for inference is investigated. This work provides effective means for implementing phase change neuromorphic processor with enhanced stability.
发布期刊链接:https://ieeexplore.ieee.org/abstract/document/9721231