Yaotian Liu, Yuhang Zhang, Qing Zhang, Rui Chen, Yongfu Li
{"title":"FEEP: Functional ECO Synthesis with Efficient Patch Minimization","authors":"Yaotian Liu, Yuhang Zhang, Qing Zhang, Rui Chen, Yongfu Li","doi":"10.1109/AICAS57966.2023.10168557","DOIUrl":null,"url":null,"abstract":"Functional engineering change order (ECO) has been an essential process in modern complex integrated circuit design. Finding a high-quality circuit patch efficiently has long been a challenge. This paper proposes FEEP, an automatic and efficient synthesis-based functional ECO method. Structural pruning and stratified searching techniques are proposed to minimize search space without extra logical equivalence checks. Moreover, we propose a machine-learning-based two-stage patch size predictor that assists in predicting patch quality. Experimental results show that our algorithm can efficiently search and produce high-quality patches under various test cases.","PeriodicalId":296649,"journal":{"name":"2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICAS57966.2023.10168557","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Functional engineering change order (ECO) has been an essential process in modern complex integrated circuit design. Finding a high-quality circuit patch efficiently has long been a challenge. This paper proposes FEEP, an automatic and efficient synthesis-based functional ECO method. Structural pruning and stratified searching techniques are proposed to minimize search space without extra logical equivalence checks. Moreover, we propose a machine-learning-based two-stage patch size predictor that assists in predicting patch quality. Experimental results show that our algorithm can efficiently search and produce high-quality patches under various test cases.