{"title":"在制品:优化算法:EDA教育的关键组成部分","authors":"F. Balasa, Safaa Mohamed","doi":"10.1109/MSE.2017.7945083","DOIUrl":null,"url":null,"abstract":"Nowadays, electronic design automation (EDA) is a regular component of computer engineering (CE) curricula. Several EDA problems can be modeled as constrained optimizations, an area where typical CE students have an insufficient background. This paper advocates the teaching of optimization algorithms as a preliminary phase for teaching graduate-level courses on EDA topics. The emphasis should be on practice, rather than theory: this can be achieved by the simultaneous development of an optimization lab using Mathematica - a computational software based on symbolic mathematics.","PeriodicalId":339888,"journal":{"name":"2017 IEEE International Conference on Microelectronic Systems Education (MSE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"WIP: Optimization algorithms: A key component of EDA education\",\"authors\":\"F. Balasa, Safaa Mohamed\",\"doi\":\"10.1109/MSE.2017.7945083\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, electronic design automation (EDA) is a regular component of computer engineering (CE) curricula. Several EDA problems can be modeled as constrained optimizations, an area where typical CE students have an insufficient background. This paper advocates the teaching of optimization algorithms as a preliminary phase for teaching graduate-level courses on EDA topics. The emphasis should be on practice, rather than theory: this can be achieved by the simultaneous development of an optimization lab using Mathematica - a computational software based on symbolic mathematics.\",\"PeriodicalId\":339888,\"journal\":{\"name\":\"2017 IEEE International Conference on Microelectronic Systems Education (MSE)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Microelectronic Systems Education (MSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MSE.2017.7945083\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Microelectronic Systems Education (MSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSE.2017.7945083","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
WIP: Optimization algorithms: A key component of EDA education
Nowadays, electronic design automation (EDA) is a regular component of computer engineering (CE) curricula. Several EDA problems can be modeled as constrained optimizations, an area where typical CE students have an insufficient background. This paper advocates the teaching of optimization algorithms as a preliminary phase for teaching graduate-level courses on EDA topics. The emphasis should be on practice, rather than theory: this can be achieved by the simultaneous development of an optimization lab using Mathematica - a computational software based on symbolic mathematics.