{"title":"ES:预测并行系统性能的工具","authors":"J. B. Sinclair, W. P. Dawkins","doi":"10.1109/MASCOT.1994.284428","DOIUrl":null,"url":null,"abstract":"ES is a tool for estimating the execution times of parallel algorithms on MIMD parallel systems. ES allows the user to model arbitrary task execution times, explicit task precedence and synchronization constraints, resource contention among tasks, and a variety of scheduling policies for shared resources. Given a model of a parallel algorithm and a parallel system, ES constructs a sequencing tree that represents some or all of the possible sequences of events that may occur during the execution of the algorithm on the system, and uses it to estimate the mean and standard deviation of the execution time of the parallel algorithm. The authors compare estimates generated by ES to measurements made of a parallel mergesort executing on an Intel iPSC/860 hypercube.<<ETX>>","PeriodicalId":288344,"journal":{"name":"Proceedings of International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"ES: a tool for predicting the performance of parallel systems\",\"authors\":\"J. B. Sinclair, W. P. Dawkins\",\"doi\":\"10.1109/MASCOT.1994.284428\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ES is a tool for estimating the execution times of parallel algorithms on MIMD parallel systems. ES allows the user to model arbitrary task execution times, explicit task precedence and synchronization constraints, resource contention among tasks, and a variety of scheduling policies for shared resources. Given a model of a parallel algorithm and a parallel system, ES constructs a sequencing tree that represents some or all of the possible sequences of events that may occur during the execution of the algorithm on the system, and uses it to estimate the mean and standard deviation of the execution time of the parallel algorithm. The authors compare estimates generated by ES to measurements made of a parallel mergesort executing on an Intel iPSC/860 hypercube.<<ETX>>\",\"PeriodicalId\":288344,\"journal\":{\"name\":\"Proceedings of International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-01-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MASCOT.1994.284428\",\"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 of International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MASCOT.1994.284428","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ES: a tool for predicting the performance of parallel systems
ES is a tool for estimating the execution times of parallel algorithms on MIMD parallel systems. ES allows the user to model arbitrary task execution times, explicit task precedence and synchronization constraints, resource contention among tasks, and a variety of scheduling policies for shared resources. Given a model of a parallel algorithm and a parallel system, ES constructs a sequencing tree that represents some or all of the possible sequences of events that may occur during the execution of the algorithm on the system, and uses it to estimate the mean and standard deviation of the execution time of the parallel algorithm. The authors compare estimates generated by ES to measurements made of a parallel mergesort executing on an Intel iPSC/860 hypercube.<>
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