{"title":"机器学习在电子设计自动化中的机会","authors":"P. Beerel, Massoud Pedram","doi":"10.1109/ISCAS.2018.8351731","DOIUrl":null,"url":null,"abstract":"The rise of machine learning (ML) has introduced many opportunities for computer-aided-design, VLSI design, and their intersection. Related to computer-aided design, we review several classical CAD algorithms which can benefit from ML, outline the key challenges, and discuss promising approaches. In particular, because some of the existing ML accelerators have used asynchronous design, we review the state-of-the-art in asynchronous CAD support, and identify opportunities for ML within these flows.","PeriodicalId":6569,"journal":{"name":"2018 IEEE International Symposium on Circuits and Systems (ISCAS)","volume":"28 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Opportunities for Machine Learning in Electronic Design Automation\",\"authors\":\"P. Beerel, Massoud Pedram\",\"doi\":\"10.1109/ISCAS.2018.8351731\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rise of machine learning (ML) has introduced many opportunities for computer-aided-design, VLSI design, and their intersection. Related to computer-aided design, we review several classical CAD algorithms which can benefit from ML, outline the key challenges, and discuss promising approaches. In particular, because some of the existing ML accelerators have used asynchronous design, we review the state-of-the-art in asynchronous CAD support, and identify opportunities for ML within these flows.\",\"PeriodicalId\":6569,\"journal\":{\"name\":\"2018 IEEE International Symposium on Circuits and Systems (ISCAS)\",\"volume\":\"28 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Symposium on Circuits and Systems (ISCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCAS.2018.8351731\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Symposium on Circuits and Systems (ISCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAS.2018.8351731","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Opportunities for Machine Learning in Electronic Design Automation
The rise of machine learning (ML) has introduced many opportunities for computer-aided-design, VLSI design, and their intersection. Related to computer-aided design, we review several classical CAD algorithms which can benefit from ML, outline the key challenges, and discuss promising approaches. In particular, because some of the existing ML accelerators have used asynchronous design, we review the state-of-the-art in asynchronous CAD support, and identify opportunities for ML within these flows.