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

In‐Memory Search for Highly Efficient Image Retrieval
发布时间:2023-08-21  点击次数:

论文类型:期刊论文
第一作者:余颖洁
通讯作者:李祎
合写作者:赵锐哲,童浩
发表刊物:Advanced Intelligent Systems
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:5
期号:3
页面范围:2200268
关键字:In-Memory Search,Highly Efficient,memristor-based CAM
DOI码:10.1002/aisy.202200268
发表时间:4494-05-01
摘要:Finding similar images in real time plays a key role in information retrieval and serves as an indispensable function of the search engine. However, image retrieval involves massive distance computation. With the increase in image data volume and dimension, distance computation is suffering from huge power consumption and high computational complexity. Despite the remarkable advantages in energy efficiency shown by nonvolatile content addressable memory (nvCAM)-based in-memory search, achieving software-comparable search accuracy remains a critical challenge under the impact of device variations and other nonideal factors. Here, a heterogeneous image retrieval system combining highly parallel in-memory search with a high-precision digital system is reported. Hamming distance (HD) can be calculated in situ with a few memory read operations on the memristor-based CAM, and several similar images are fetched for further high-precision rerank in the digital system. This heterogeneous computing system shows high energy efficiency (50×) compared to the CPU and higher search accuracy than the fully in-memory computing method, thus alleviating the efficiency bottleneck of CPU-based image retrieval.
发布期刊链接:https://onlinelibrary.wiley.com/doi/full/10.1002/aisy.202200268