{"title":"时间和成本驱动的MPI程序在云环境下执行的自治框架","authors":"Aarthi Raveendran, Tekin Bicer, G. Agrawal","doi":"10.1109/Grid.2011.36","DOIUrl":null,"url":null,"abstract":"This paper gives an overview of a framework for making existing MPI applications elastic, and executing them with user-specified time and cost constraints in a cloud framework. Considering the limitations of the MPI implementations currently available, we support adaptation by terminating one execution and restarting a new program on a different number of instances. The key component of our system is a decision layer. Based on the time and cost constraints, this layer decides whether to use fewer or a larger number of instances for the applications, and when appropriate, chooses to migrate the application to a different type of instance. Among other factors, the decision layer also models the redistribution costs.","PeriodicalId":308086,"journal":{"name":"2011 IEEE/ACM 12th International Conference on Grid Computing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Autonomic Framework for Time and Cost Driven Execution of MPI Programs on Cloud Environments\",\"authors\":\"Aarthi Raveendran, Tekin Bicer, G. Agrawal\",\"doi\":\"10.1109/Grid.2011.36\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper gives an overview of a framework for making existing MPI applications elastic, and executing them with user-specified time and cost constraints in a cloud framework. Considering the limitations of the MPI implementations currently available, we support adaptation by terminating one execution and restarting a new program on a different number of instances. The key component of our system is a decision layer. Based on the time and cost constraints, this layer decides whether to use fewer or a larger number of instances for the applications, and when appropriate, chooses to migrate the application to a different type of instance. Among other factors, the decision layer also models the redistribution costs.\",\"PeriodicalId\":308086,\"journal\":{\"name\":\"2011 IEEE/ACM 12th International Conference on Grid Computing\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE/ACM 12th International Conference on Grid Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/Grid.2011.36\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE/ACM 12th International Conference on Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Grid.2011.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Autonomic Framework for Time and Cost Driven Execution of MPI Programs on Cloud Environments
This paper gives an overview of a framework for making existing MPI applications elastic, and executing them with user-specified time and cost constraints in a cloud framework. Considering the limitations of the MPI implementations currently available, we support adaptation by terminating one execution and restarting a new program on a different number of instances. The key component of our system is a decision layer. Based on the time and cost constraints, this layer decides whether to use fewer or a larger number of instances for the applications, and when appropriate, chooses to migrate the application to a different type of instance. Among other factors, the decision layer also models the redistribution costs.