Hiroki Nishikawa, Kaname Shimada, Ittetsu Taniguchi, H. Tomiyama
{"title":"Energy-aware scheduling of malleable fork-join tasks under a deadline constraint on heterogeneous multicores","authors":"Hiroki Nishikawa, Kaname Shimada, Ittetsu Taniguchi, H. Tomiyama","doi":"10.1145/3373400.3373409","DOIUrl":null,"url":null,"abstract":"This paper proposes an energy-aware scheduling of malleable fork-join (MFJ) tasks on heterogeneous multicores. This work allows a task to be split into multiple sub-tasks for fork-join parallel execution. The number of the sub-tasks is determined simultaneously with scheduling. Our scheduling technique aims at the minimization of energy consumption under a deadline constraint. In addition, this paper proposes a technique for simultaneous scheduling and core-type optimization. The technique optimally decides types of cores (to be either \"big\" or \"little\") at the same time as MFJ task scheduling in order to further reduce energy consumption.","PeriodicalId":447904,"journal":{"name":"SIGBED Rev.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGBED Rev.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3373400.3373409","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper proposes an energy-aware scheduling of malleable fork-join (MFJ) tasks on heterogeneous multicores. This work allows a task to be split into multiple sub-tasks for fork-join parallel execution. The number of the sub-tasks is determined simultaneously with scheduling. Our scheduling technique aims at the minimization of energy consumption under a deadline constraint. In addition, this paper proposes a technique for simultaneous scheduling and core-type optimization. The technique optimally decides types of cores (to be either "big" or "little") at the same time as MFJ task scheduling in order to further reduce energy consumption.