CSpace  > 中国科学院计算技术研究所期刊论文  > 英文
Chip design with machine learning: a survey from algorithm perspective
He, Wenkai1,2,3; Li, Xiaqing1; Song, Xinkai1,3; Hao, Yifan1,3; Zhang, Rui1,3; Du, Zidong1; Chen, Yunji1,2
2023-11-01
发表期刊SCIENCE CHINA-INFORMATION SCIENCES
ISSN1674-733X
卷号66期号:11页码:31
摘要Chip design with machine learning (ML) has been widely explored to achieve better designs, lower runtime costs, and no human-in-the-loop process. However, with tons of work, there is a lack of clear links between the ML algorithms and the target problems, causing a huge gap in understanding the potential and possibility of ML in future chip design. This paper comprehensively surveys existing studies in chip design with ML from an algorithm perspective. To achieve this goal, we first propose a novel and systematical taxonomy that divides target problems in chip design into three categories. Then, to solve the target problems with ML algorithms, we formulate the three categories as three ML problems correspondingly. Based on the taxonomy, we conduct a comprehensive survey in terms of target problems based on different ML algorithms. Finally, we conclude three key challenges for existing studies and highlight several insights for the future development of chip design with machine learning. By constructing a clear link between chip design problems and ML solutions, we hope the survey can shed light on the road to chip design intelligence from previous chip design automation.
关键词chip design machine learning chip design automation design result estimation design optimization and correction design construction
DOI10.1007/s11432-022-3772-8
收录类别SCI
语种英语
资助项目This work was partially supported by National Natural Science Foundation of China (Grant Nos. 61925208, 62222214, 62102399, U22A2028, U19B2019), Beijing Academy of Artificial Intelligence (BAAI), CAS Project for Young Scientists in Basic Research (Grant No[61925208] ; This work was partially supported by National Natural Science Foundation of China (Grant Nos. 61925208, 62222214, 62102399, U22A2028, U19B2019), Beijing Academy of Artificial Intelligence (BAAI), CAS Project for Young Scientists in Basic Research (Grant No[62222214] ; This work was partially supported by National Natural Science Foundation of China (Grant Nos. 61925208, 62222214, 62102399, U22A2028, U19B2019), Beijing Academy of Artificial Intelligence (BAAI), CAS Project for Young Scientists in Basic Research (Grant No[62102399] ; This work was partially supported by National Natural Science Foundation of China (Grant Nos. 61925208, 62222214, 62102399, U22A2028, U19B2019), Beijing Academy of Artificial Intelligence (BAAI), CAS Project for Young Scientists in Basic Research (Grant No[U22A2028] ; This work was partially supported by National Natural Science Foundation of China (Grant Nos. 61925208, 62222214, 62102399, U22A2028, U19B2019), Beijing Academy of Artificial Intelligence (BAAI), CAS Project for Young Scientists in Basic Research (Grant No[U19B2019] ; National Natural Science Foundation of China[YSBR-029] ; CAS Project for Young Scientists in Basic Research ; Youth Innovation Promotion Association CAS and Xplore Prize
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS记录号WOS:001090428200002
出版者SCIENCE PRESS
引用统计
文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/21094
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Chen, Yunji
作者单位1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Processor, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Cambricon Technol, Beijing 100191, Peoples R China
推荐引用方式
GB/T 7714
He, Wenkai,Li, Xiaqing,Song, Xinkai,et al. Chip design with machine learning: a survey from algorithm perspective[J]. SCIENCE CHINA-INFORMATION SCIENCES,2023,66(11):31.
APA He, Wenkai.,Li, Xiaqing.,Song, Xinkai.,Hao, Yifan.,Zhang, Rui.,...&Chen, Yunji.(2023).Chip design with machine learning: a survey from algorithm perspective.SCIENCE CHINA-INFORMATION SCIENCES,66(11),31.
MLA He, Wenkai,et al."Chip design with machine learning: a survey from algorithm perspective".SCIENCE CHINA-INFORMATION SCIENCES 66.11(2023):31.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[He, Wenkai]的文章
[Li, Xiaqing]的文章
[Song, Xinkai]的文章
百度学术
百度学术中相似的文章
[He, Wenkai]的文章
[Li, Xiaqing]的文章
[Song, Xinkai]的文章
必应学术
必应学术中相似的文章
[He, Wenkai]的文章
[Li, Xiaqing]的文章
[Song, Xinkai]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。