{"title":"Early Prediction of the Cost of HPC Application Execution in the Cloud","authors":"M. Rak, Mauro Turtur, Umberto Villano","doi":"10.1109/SYNASC.2014.61","DOIUrl":null,"url":null,"abstract":"Even if clouds are not fit for high-end HPC applications, they could be profitably used to bring the power of economic and scalable parallel computing to the masses. But this requires both simple development environments, able to exploit cloud scalability, and the capability to easily predict the cost of HPC application runs. This paper presents a framework built on the top of a cloud aware programming platform (mOSAIC) for the development of bag-of-tasks scientific applications. The framework integrates a cloud-based simulation environment able to predict the behavior of the developed applications. Simulations enable the developer to predict at an early development stage performance and cloud resource usage, and so the infrastructure lease cost on a public cloud. The paper sketches the framework organization and discusses the approach followed for application development. Moreover, some validation tests of prediction results are presented.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2014.61","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Even if clouds are not fit for high-end HPC applications, they could be profitably used to bring the power of economic and scalable parallel computing to the masses. But this requires both simple development environments, able to exploit cloud scalability, and the capability to easily predict the cost of HPC application runs. This paper presents a framework built on the top of a cloud aware programming platform (mOSAIC) for the development of bag-of-tasks scientific applications. The framework integrates a cloud-based simulation environment able to predict the behavior of the developed applications. Simulations enable the developer to predict at an early development stage performance and cloud resource usage, and so the infrastructure lease cost on a public cloud. The paper sketches the framework organization and discusses the approach followed for application development. Moreover, some validation tests of prediction results are presented.