A. Sena, A. P. Nascimento, J. A. D. Silva, Daniela Vianna, Cristina Boeres, Vinod E. F. Rebello
{"title":"On the Advantages of an Alternative MPI Execution Model for Grids","authors":"A. Sena, A. P. Nascimento, J. A. D. Silva, Daniela Vianna, Cristina Boeres, Vinod E. F. Rebello","doi":"10.1109/CCGRID.2007.74","DOIUrl":null,"url":null,"abstract":"The MPI message passing library is used extensively in the scientific community as a tool for parallel programming. Even though improvements have been made to existing implementations to support execution on computational grids, MPI was initially designed to deal with homogeneous, fault- free, static environments such as computing clusters. The typical programming approach is to execute a single MPI process on each resource. However, this may not be appropriate for heterogeneous, non-dedicated and dynamic environments such as grids. This paper aims to show that programmers can implement parallel MPI solutions to their problems in an architectural independent style and obtain good performance on a grid by transferring responsibility to an application management system (AMS). A comparison of program implementations under a traditional MPI execution model and a fine-grain model highlight the advantages of using the latter.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGRID.2007.74","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
The MPI message passing library is used extensively in the scientific community as a tool for parallel programming. Even though improvements have been made to existing implementations to support execution on computational grids, MPI was initially designed to deal with homogeneous, fault- free, static environments such as computing clusters. The typical programming approach is to execute a single MPI process on each resource. However, this may not be appropriate for heterogeneous, non-dedicated and dynamic environments such as grids. This paper aims to show that programmers can implement parallel MPI solutions to their problems in an architectural independent style and obtain good performance on a grid by transferring responsibility to an application management system (AMS). A comparison of program implementations under a traditional MPI execution model and a fine-grain model highlight the advantages of using the latter.