{"title":"Extending OmpSs to Support Data Analytics Workload","authors":"Marcos Maroñas","doi":"10.1109/HPCS.2017.136","DOIUrl":null,"url":null,"abstract":"In the era of big data, new scientific applications such as those used in astronomy [1] are emerging and challenging High Performance Computing (HPC) systems and software. Traditionally, HPC applications were compute-bounded, with a light use of the I/O capabilites at the start and end of the execution. In contrast, emergent applications present data- intensive behaviors arising several new challenges to be faced by hardware and software.","PeriodicalId":115758,"journal":{"name":"2017 International Conference on High Performance Computing & Simulation (HPCS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on High Performance Computing & Simulation (HPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCS.2017.136","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the era of big data, new scientific applications such as those used in astronomy [1] are emerging and challenging High Performance Computing (HPC) systems and software. Traditionally, HPC applications were compute-bounded, with a light use of the I/O capabilites at the start and end of the execution. In contrast, emergent applications present data- intensive behaviors arising several new challenges to be faced by hardware and software.