{"title":"使用P个可能失败的处理器执行N个任务的并行系统的分析性能模型","authors":"G. Weerasinghe, Imad Antonios, L. Lipsky","doi":"10.1109/NCA.2001.962547","DOIUrl":null,"url":null,"abstract":"We present a Markov model for analyzing the performance of parallel/distributed processors that execute a job consisting of N independent tasks in parallel using P processors. The model is a Markov chain with states representing service and failure rates with k (0<k/spl les/P) active processors. The task-times and processor failures are both exponentially distributed. We derive a number of expressions to determine the mean execution time, probability of success, work, and other measurable quantities, all conditioned on the job finishing successfully. A prototype, implemented using an extended version of ACMPI, is used for actual experiments that are based on simulated task-times and processor failures. We present our results comparing the analytic model with the prototype for a range of values of processor failure rates. We also discuss extensions of the model and issues related to communication costs, approximations and effect of task-time distributions.","PeriodicalId":385607,"journal":{"name":"Proceedings IEEE International Symposium on Network Computing and Applications. NCA 2001","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"An analytic performance model of parallel systems that perform N tasks using P processors that can fail\",\"authors\":\"G. Weerasinghe, Imad Antonios, L. Lipsky\",\"doi\":\"10.1109/NCA.2001.962547\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a Markov model for analyzing the performance of parallel/distributed processors that execute a job consisting of N independent tasks in parallel using P processors. The model is a Markov chain with states representing service and failure rates with k (0<k/spl les/P) active processors. The task-times and processor failures are both exponentially distributed. We derive a number of expressions to determine the mean execution time, probability of success, work, and other measurable quantities, all conditioned on the job finishing successfully. A prototype, implemented using an extended version of ACMPI, is used for actual experiments that are based on simulated task-times and processor failures. We present our results comparing the analytic model with the prototype for a range of values of processor failure rates. We also discuss extensions of the model and issues related to communication costs, approximations and effect of task-time distributions.\",\"PeriodicalId\":385607,\"journal\":{\"name\":\"Proceedings IEEE International Symposium on Network Computing and Applications. NCA 2001\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-10-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE International Symposium on Network Computing and Applications. NCA 2001\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCA.2001.962547\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings IEEE International Symposium on Network Computing and Applications. NCA 2001","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCA.2001.962547","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An analytic performance model of parallel systems that perform N tasks using P processors that can fail
We present a Markov model for analyzing the performance of parallel/distributed processors that execute a job consisting of N independent tasks in parallel using P processors. The model is a Markov chain with states representing service and failure rates with k (0
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