{"title":"ETAHM: An energy-aware task allocation algorithm for heterogeneous multiprocessor","authors":"Po-Chun Chang, I-Wei Wu, J. Shann, C. Chung","doi":"10.1145/1391469.1391667","DOIUrl":null,"url":null,"abstract":"In demand of more computing power and less energy use, multiprocessor with power management facility emerges in embedded system design. Dynamic voltage scaling is such a facility that varies clock speed and supply voltage to save more energy. In this paper, we propose ETAHM to allocate tasks on a target multiprocessor system. In pursuit of global optimal solution, it mixes task scheduling, mapping and DVS utilization in one phase and couples ant colony optimization algorithm. Extensive experiments show ETAHM could save 22.71% more energy than CASPER (V. Kianzad et al., 2005), a state-of-the-art integrated framework that tackles the identical problem with genetic algorithm instead.","PeriodicalId":412696,"journal":{"name":"2008 45th ACM/IEEE Design Automation Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"48","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 45th ACM/IEEE Design Automation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1391469.1391667","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 48
Abstract
In demand of more computing power and less energy use, multiprocessor with power management facility emerges in embedded system design. Dynamic voltage scaling is such a facility that varies clock speed and supply voltage to save more energy. In this paper, we propose ETAHM to allocate tasks on a target multiprocessor system. In pursuit of global optimal solution, it mixes task scheduling, mapping and DVS utilization in one phase and couples ant colony optimization algorithm. Extensive experiments show ETAHM could save 22.71% more energy than CASPER (V. Kianzad et al., 2005), a state-of-the-art integrated framework that tackles the identical problem with genetic algorithm instead.