Yong-sheng Li, E. Li, Huan Yu, Hanju Oh, Muhannad S. Bakir, Madhavan Swaminathan
{"title":"3D-IC电-热模拟与管理的机器学习","authors":"Yong-sheng Li, E. Li, Huan Yu, Hanju Oh, Muhannad S. Bakir, Madhavan Swaminathan","doi":"10.1109/COMPEM.2018.8496543","DOIUrl":null,"url":null,"abstract":"Thermal management for 3-D ICs is not only important but also challenging. While air-cooled heat sink is agreed to become incapable for 3-D ICs, microchannel cooling has provided a better solution. In this paper, a machine learning method, Bayesian Optimization (BO), is applied in 3-D ICs with a time-dependent power map to intelligently control the flow rates of the tier-specific microfluidic heatsink (MFHS) for dynamic thermal management (DTM).","PeriodicalId":221352,"journal":{"name":"2018 IEEE International Conference on Computational Electromagnetics (ICCEM)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Machine Learning for 3D-IC Electric-Thermal Simulation and Management\",\"authors\":\"Yong-sheng Li, E. Li, Huan Yu, Hanju Oh, Muhannad S. Bakir, Madhavan Swaminathan\",\"doi\":\"10.1109/COMPEM.2018.8496543\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Thermal management for 3-D ICs is not only important but also challenging. While air-cooled heat sink is agreed to become incapable for 3-D ICs, microchannel cooling has provided a better solution. In this paper, a machine learning method, Bayesian Optimization (BO), is applied in 3-D ICs with a time-dependent power map to intelligently control the flow rates of the tier-specific microfluidic heatsink (MFHS) for dynamic thermal management (DTM).\",\"PeriodicalId\":221352,\"journal\":{\"name\":\"2018 IEEE International Conference on Computational Electromagnetics (ICCEM)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Computational Electromagnetics (ICCEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPEM.2018.8496543\",\"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 Conference on Computational Electromagnetics (ICCEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPEM.2018.8496543","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Machine Learning for 3D-IC Electric-Thermal Simulation and Management
Thermal management for 3-D ICs is not only important but also challenging. While air-cooled heat sink is agreed to become incapable for 3-D ICs, microchannel cooling has provided a better solution. In this paper, a machine learning method, Bayesian Optimization (BO), is applied in 3-D ICs with a time-dependent power map to intelligently control the flow rates of the tier-specific microfluidic heatsink (MFHS) for dynamic thermal management (DTM).