{"title":"Improved Data-Aware Task Dispatching for Batch Queuing Systems","authors":"Xieming Li, O. Tatebe","doi":"10.1109/DATACLOUD.2016.9","DOIUrl":null,"url":null,"abstract":"This paper describes a data-aware task dispatching strategy called Improved Data-Aware Task Dispatching (IDAD). This approach exploits the high-performance of local file access in non-uniform storage-access (NUSA) file systems and is based on our previous work, Data-Aware Dispatch (DAD). In IDAD, the method of calculating data placement is revised, and the CPU factor is removed, as it has no major impact on performance but significantly reduces the difficulty for tweaking parameter.We evaluated our approach in comparison with DAD and the stock FIFO Torque scheduler using BLAST benchmarks. We observed makespan reductions of 10.40% and 35.05% compared with DAD and stock FIFO schedulers, respectively.","PeriodicalId":325593,"journal":{"name":"2016 Seventh International Workshop on Data-Intensive Computing in the Clouds (DataCloud)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Seventh International Workshop on Data-Intensive Computing in the Clouds (DataCloud)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DATACLOUD.2016.9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper describes a data-aware task dispatching strategy called Improved Data-Aware Task Dispatching (IDAD). This approach exploits the high-performance of local file access in non-uniform storage-access (NUSA) file systems and is based on our previous work, Data-Aware Dispatch (DAD). In IDAD, the method of calculating data placement is revised, and the CPU factor is removed, as it has no major impact on performance but significantly reduces the difficulty for tweaking parameter.We evaluated our approach in comparison with DAD and the stock FIFO Torque scheduler using BLAST benchmarks. We observed makespan reductions of 10.40% and 35.05% compared with DAD and stock FIFO schedulers, respectively.