{"title":"QoS-Driven Coordinated Management of Resources to Save Energy in Multi-core Systems","authors":"M. Nejat, M. Pericàs, P. Stenström","doi":"10.1109/IPDPS.2019.00040","DOIUrl":null,"url":null,"abstract":"Applications that are run on multicore systems without performance targets can waste significant energy. This paper considers, for the first time, a QoS-driven coordinated resource management algorithm (RMA) that dynamically adjusts the size of the per-core last-level cache partitions and the per-core voltage-frequency settings to save energy while respecting QoS requirements of individual applications in multi-programmed workloads run on multi-core systems. It does so by doing configuration-space exploration across the spectrum of LLC partition sizes and DVFS settings at runtime at negligible overhead. Compared to DVFS and cache partitioning alone, we show that our proposed coordinated RMA is capable of saving, on average, 20% energy as compared to 15% for DVFS alone and 7% for cache partitioning alone, when the performance target is set to 70% of the baseline system performance.","PeriodicalId":403406,"journal":{"name":"2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPS.2019.00040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Applications that are run on multicore systems without performance targets can waste significant energy. This paper considers, for the first time, a QoS-driven coordinated resource management algorithm (RMA) that dynamically adjusts the size of the per-core last-level cache partitions and the per-core voltage-frequency settings to save energy while respecting QoS requirements of individual applications in multi-programmed workloads run on multi-core systems. It does so by doing configuration-space exploration across the spectrum of LLC partition sizes and DVFS settings at runtime at negligible overhead. Compared to DVFS and cache partitioning alone, we show that our proposed coordinated RMA is capable of saving, on average, 20% energy as compared to 15% for DVFS alone and 7% for cache partitioning alone, when the performance target is set to 70% of the baseline system performance.