{"title":"Environmental-aware optimization of MPI checkpointing intervals","authors":"H. Jitsumoto, Toshio Endo, S. Matsuoka","doi":"10.1109/CLUSTR.2008.4663790","DOIUrl":null,"url":null,"abstract":"Fault-tolerance for HPC systems with long-running applications of massive and growing scale is now essential. Although checkpointing with rollback recovery is a popular technique, automated checkpointing is becoming troublesome in a real system, due to the extremely large size of collective application memory. Therefore, automated optimization of the checkpoint interval is essential, but the optimal point depends on hardware failure rates and I/O bandwidth. Our new model and an algorithm, which is an extension of Vaidyapsilas model, solve the problem by taking such parameters into account. Prototype implementation on our fault-tolerant MPI framework ABARIS showed approximately 5.5% improvement over statically user-determined cases.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Cluster Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLUSTR.2008.4663790","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
Fault-tolerance for HPC systems with long-running applications of massive and growing scale is now essential. Although checkpointing with rollback recovery is a popular technique, automated checkpointing is becoming troublesome in a real system, due to the extremely large size of collective application memory. Therefore, automated optimization of the checkpoint interval is essential, but the optimal point depends on hardware failure rates and I/O bandwidth. Our new model and an algorithm, which is an extension of Vaidyapsilas model, solve the problem by taking such parameters into account. Prototype implementation on our fault-tolerant MPI framework ABARIS showed approximately 5.5% improvement over statically user-determined cases.