{"title":"Towards a High Level Programming Paradigm to Deploy e-Science Applications with Dynamic Workflows on Large Scale Distributed Systems","authors":"M. B. Belgacem, N. Abdennadher","doi":"10.1109/CCGrid.2015.147","DOIUrl":null,"url":null,"abstract":"This papers targeted scientists and programmers who need to easily develop and run e-science applications on large scale distributed systems. We present a rich programming paradigm and environment used to develop and deploy high performance applications (HPC) on large scale distributed and heterogeneous platforms. We particularly target iterative e-science applications where (i) convergence conditions and number of jobs are not known in advance, (ii) jobs are created on the fly and (iii) jobs could be persistent. We propose two programming paradigms so as to provide intuitive statements enabling an easy writing of HPC e-science applications. Non-expert developers (scientific researchers) can use them to guarantee fast development and efficient deployment of their applications.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"6 1","pages":"292-301"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGrid.2015.147","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
This papers targeted scientists and programmers who need to easily develop and run e-science applications on large scale distributed systems. We present a rich programming paradigm and environment used to develop and deploy high performance applications (HPC) on large scale distributed and heterogeneous platforms. We particularly target iterative e-science applications where (i) convergence conditions and number of jobs are not known in advance, (ii) jobs are created on the fly and (iii) jobs could be persistent. We propose two programming paradigms so as to provide intuitive statements enabling an easy writing of HPC e-science applications. Non-expert developers (scientific researchers) can use them to guarantee fast development and efficient deployment of their applications.