{"title":"Particle Swarm Optimization guided multi-frequency power-aware System-on-Chip test scheduling using window-based peak power model","authors":"R. Karmakar, Aditya Agarwal, S. Chattopadhyay","doi":"10.1109/ISVDAT.2014.6881089","DOIUrl":null,"url":null,"abstract":"This paper presents a multi-frequency test scheduling strategy for System-on-chip (SoC) under power constraint. While existing approaches consider either global peak or cycle-accurate power model, the proposed work considers an intermediate approach to reduce the power overestimation of global peak power model as well as the computational complexity of cycle-accurate power model. A Particle Swarm Optimization (PSO) guided test scheduling strategy has been integrated with our new window-based peak power model to reduce Test Application Time (TAT) over global peak power model. Experimental results show that further improvement in TAT can be achieved using multi-frequency test environment over single-frequency test approach.","PeriodicalId":217280,"journal":{"name":"18th International Symposium on VLSI Design and Test","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th International Symposium on VLSI Design and Test","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISVDAT.2014.6881089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper presents a multi-frequency test scheduling strategy for System-on-chip (SoC) under power constraint. While existing approaches consider either global peak or cycle-accurate power model, the proposed work considers an intermediate approach to reduce the power overestimation of global peak power model as well as the computational complexity of cycle-accurate power model. A Particle Swarm Optimization (PSO) guided test scheduling strategy has been integrated with our new window-based peak power model to reduce Test Application Time (TAT) over global peak power model. Experimental results show that further improvement in TAT can be achieved using multi-frequency test environment over single-frequency test approach.