H. Kanemitsu, M. Hanada, Takashige Hoshiai, H. Nakazato
{"title":"Effective use of computational resources in multicore distributed systems","authors":"H. Kanemitsu, M. Hanada, Takashige Hoshiai, H. Nakazato","doi":"10.1109/ICACT.2014.6779187","DOIUrl":null,"url":null,"abstract":"In the last decades, many kinds of task execution models such as grid and cloud computing have been developed. In such distributed systems, each task is processed by respective processor in multicored computers e.g., household PCs which we can easily harness in recent years. If there is one policy to automatically decide the “best” combination and the number of processors (and computers), we effectively utilize those computational resources, thereby large number of jobs can be executed in parallel. In this paper, we propose a method for mapping of execution units for such environments. The method adopts a remapping technology after processor-execution unit mapping[6] is finished. Experimental comparisons by a simulation show the advantages of the proposed method.","PeriodicalId":118033,"journal":{"name":"2013 15th International Conference on Advanced Communications Technology (ICACT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 15th International Conference on Advanced Communications Technology (ICACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACT.2014.6779187","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In the last decades, many kinds of task execution models such as grid and cloud computing have been developed. In such distributed systems, each task is processed by respective processor in multicored computers e.g., household PCs which we can easily harness in recent years. If there is one policy to automatically decide the “best” combination and the number of processors (and computers), we effectively utilize those computational resources, thereby large number of jobs can be executed in parallel. In this paper, we propose a method for mapping of execution units for such environments. The method adopts a remapping technology after processor-execution unit mapping[6] is finished. Experimental comparisons by a simulation show the advantages of the proposed method.