{"title":"Exploring resource mapping policies for dynamic clustering on NoC-based MPSoCs","authors":"Gustavo Girão, Thiago Santini, F. Wagner","doi":"10.7873/DATE.2013.147","DOIUrl":null,"url":null,"abstract":"The dramatic increase in the number of processors, memories and other components in the same chip calls for resource-aware mechanisms to improve performance. This paper proposes four different resource mapping policies for NoC-based MPSoCs that leverage on distinct aspects of the parallel nature of the applications and on architecture constraints, such as off-chip memory latency. Results show that the use of these policies can improve performance up to 22.5% in average, and, in some cases, depending on the parallel programming model of each application, the improvement may reach up to 32%.","PeriodicalId":6310,"journal":{"name":"2013 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"132 1","pages":"681-684"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Design, Automation & Test in Europe Conference & Exhibition (DATE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7873/DATE.2013.147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The dramatic increase in the number of processors, memories and other components in the same chip calls for resource-aware mechanisms to improve performance. This paper proposes four different resource mapping policies for NoC-based MPSoCs that leverage on distinct aspects of the parallel nature of the applications and on architecture constraints, such as off-chip memory latency. Results show that the use of these policies can improve performance up to 22.5% in average, and, in some cases, depending on the parallel programming model of each application, the improvement may reach up to 32%.