Yang Xiao, James Alfred Walker, S. Bale, M. Trefzer, A. Tyrrell
{"title":"电路设计优化使用改进的遗传算法和器件布局主题","authors":"Yang Xiao, James Alfred Walker, S. Bale, M. Trefzer, A. Tyrrell","doi":"10.1109/ICES.2014.7008715","DOIUrl":null,"url":null,"abstract":"Circuit performance optimisation such as increasing speed and minimizing power consumption is the most important design goal for circuit designers next to correct functionality. This is generally also a very complex problem where, in order to solve it, several factors such as device characteristics, circuit topology, and circuit functionality must be considered. Particularly, as technology has scaled to the atomistic level, the resulting uncertainty factors further affect circuit performance. In this paper, we propose combining a modified genetic algorithm with dynamic gene mutation and device layout motif selection for circuit performance improvement. We explore novel device layout motifs (O shape device) to exploit effects of device layout at the atomistic level in order to improve characteristics of circuits and combine them with a modified GA for automatic circuit optimisation. Additionally, in order to overcome local optima and premature convergence, a dynamic gene mutation rate is performed within the GA. The experimental results show that this methodology can achieve more than 30% delay reduction through mixed combinations of O shape devices and regular devices in a circuit, compared to circuits built of only regular devices. At the same time, the local optima are also reliably avoided due to the dynamic gene mutation.","PeriodicalId":432958,"journal":{"name":"2014 IEEE International Conference on Evolvable Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Circuit design optimisation using a modified genetic algorithm and device layout motifs\",\"authors\":\"Yang Xiao, James Alfred Walker, S. Bale, M. Trefzer, A. Tyrrell\",\"doi\":\"10.1109/ICES.2014.7008715\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Circuit performance optimisation such as increasing speed and minimizing power consumption is the most important design goal for circuit designers next to correct functionality. This is generally also a very complex problem where, in order to solve it, several factors such as device characteristics, circuit topology, and circuit functionality must be considered. Particularly, as technology has scaled to the atomistic level, the resulting uncertainty factors further affect circuit performance. In this paper, we propose combining a modified genetic algorithm with dynamic gene mutation and device layout motif selection for circuit performance improvement. We explore novel device layout motifs (O shape device) to exploit effects of device layout at the atomistic level in order to improve characteristics of circuits and combine them with a modified GA for automatic circuit optimisation. Additionally, in order to overcome local optima and premature convergence, a dynamic gene mutation rate is performed within the GA. The experimental results show that this methodology can achieve more than 30% delay reduction through mixed combinations of O shape devices and regular devices in a circuit, compared to circuits built of only regular devices. At the same time, the local optima are also reliably avoided due to the dynamic gene mutation.\",\"PeriodicalId\":432958,\"journal\":{\"name\":\"2014 IEEE International Conference on Evolvable Systems\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Conference on Evolvable Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICES.2014.7008715\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Evolvable Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICES.2014.7008715","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Circuit design optimisation using a modified genetic algorithm and device layout motifs
Circuit performance optimisation such as increasing speed and minimizing power consumption is the most important design goal for circuit designers next to correct functionality. This is generally also a very complex problem where, in order to solve it, several factors such as device characteristics, circuit topology, and circuit functionality must be considered. Particularly, as technology has scaled to the atomistic level, the resulting uncertainty factors further affect circuit performance. In this paper, we propose combining a modified genetic algorithm with dynamic gene mutation and device layout motif selection for circuit performance improvement. We explore novel device layout motifs (O shape device) to exploit effects of device layout at the atomistic level in order to improve characteristics of circuits and combine them with a modified GA for automatic circuit optimisation. Additionally, in order to overcome local optima and premature convergence, a dynamic gene mutation rate is performed within the GA. The experimental results show that this methodology can achieve more than 30% delay reduction through mixed combinations of O shape devices and regular devices in a circuit, compared to circuits built of only regular devices. At the same time, the local optima are also reliably avoided due to the dynamic gene mutation.