Institute of Computing Technology, Chinese Academy IR
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 |
ISSN | 1674-733X |
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 |
DOI | 10.1007/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. |
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