{"title":"Simple yet Efficient Deployment of Scientific Applications in the Cloud","authors":"Leyi Sun, Yifan Zhuo, O. Marin","doi":"10.1109/ICPADS53394.2021.00106","DOIUrl":null,"url":null,"abstract":"Scientific applications can benefit greatly from getting deployed on a cloud computing platform, but such deployments require skills and expertise that are beyond the reach of many scientists. We address this issue with a framework that simplifies the process of writing cloud-ready scientific applications, and that automates their deployment and execution on top of cloud infrastructures. This paper presents (1) our domain-specific language whose syntax is simple to learn and use, and (2) our compiler that exploits potential data parallelism opportunities and handles load balancing automatically for the users. Our framework prototype demonstrates the feasibility of our approach, and our scalability analysis looks promising.","PeriodicalId":309508,"journal":{"name":"2021 IEEE 27th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 27th International Conference on Parallel and Distributed Systems (ICPADS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPADS53394.2021.00106","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
Scientific applications can benefit greatly from getting deployed on a cloud computing platform, but such deployments require skills and expertise that are beyond the reach of many scientists. We address this issue with a framework that simplifies the process of writing cloud-ready scientific applications, and that automates their deployment and execution on top of cloud infrastructures. This paper presents (1) our domain-specific language whose syntax is simple to learn and use, and (2) our compiler that exploits potential data parallelism opportunities and handles load balancing automatically for the users. Our framework prototype demonstrates the feasibility of our approach, and our scalability analysis looks promising.