{"title":"A hybrid framework for application allocation and scheduling in multicore systems with energy harvesting","authors":"Yi Xiang, S. Pasricha","doi":"10.1145/2591513.2591527","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a novel hybrid design-time and run-time framework for allocating and scheduling applications in multi-core embedded systems with solar energy harvesting. Due to limited energy availability at run-time, our framework offloads scheduling complexity to design time by creating energy-efficient schedule templates for varying energy budget levels, which are selected at run-time in a manner that is contingent on the available harvested energy and executed with a lightweight slack reclamation scheme that extracts additional energy savings. Our experimental results show that the proposed framework produces energy-efficient and dependency-aware schedules to execute applications under varying and stringent energy constraints, with 23-40% lower miss rates than in prior works on harvesting energy-aware scheduling.","PeriodicalId":272619,"journal":{"name":"ACM Great Lakes Symposium on VLSI","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Great Lakes Symposium on VLSI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2591513.2591527","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this paper, we propose a novel hybrid design-time and run-time framework for allocating and scheduling applications in multi-core embedded systems with solar energy harvesting. Due to limited energy availability at run-time, our framework offloads scheduling complexity to design time by creating energy-efficient schedule templates for varying energy budget levels, which are selected at run-time in a manner that is contingent on the available harvested energy and executed with a lightweight slack reclamation scheme that extracts additional energy savings. Our experimental results show that the proposed framework produces energy-efficient and dependency-aware schedules to execute applications under varying and stringent energy constraints, with 23-40% lower miss rates than in prior works on harvesting energy-aware scheduling.