{"title":"场景感知流应用的性能分析工具","authors":"B. Theelen","doi":"10.1109/QEST.2007.7","DOIUrl":null,"url":null,"abstract":"Dataflow models are often used for analysing streaming applications. The recently introduced scenario-aware extension of the synchronous dataflow model can capture the dynamism in computation and communication resource requirements of streaming applications that originates from different modes of operation (scenarios). This scenario-aware dataflow model uses a probabilistic approach to express the order in which scenarios (and different execution times within a scenario) occur. This paper discusses a tool for exhaustive and simulation-based analysis of various important performance metrics for scenario-aware streaming applications.","PeriodicalId":249627,"journal":{"name":"Fourth International Conference on the Quantitative Evaluation of Systems (QEST 2007)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"A Performance Analysis Tool for Scenario-Aware Streaming Applications\",\"authors\":\"B. Theelen\",\"doi\":\"10.1109/QEST.2007.7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dataflow models are often used for analysing streaming applications. The recently introduced scenario-aware extension of the synchronous dataflow model can capture the dynamism in computation and communication resource requirements of streaming applications that originates from different modes of operation (scenarios). This scenario-aware dataflow model uses a probabilistic approach to express the order in which scenarios (and different execution times within a scenario) occur. This paper discusses a tool for exhaustive and simulation-based analysis of various important performance metrics for scenario-aware streaming applications.\",\"PeriodicalId\":249627,\"journal\":{\"name\":\"Fourth International Conference on the Quantitative Evaluation of Systems (QEST 2007)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fourth International Conference on the Quantitative Evaluation of Systems (QEST 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QEST.2007.7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fourth International Conference on the Quantitative Evaluation of Systems (QEST 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QEST.2007.7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Performance Analysis Tool for Scenario-Aware Streaming Applications
Dataflow models are often used for analysing streaming applications. The recently introduced scenario-aware extension of the synchronous dataflow model can capture the dynamism in computation and communication resource requirements of streaming applications that originates from different modes of operation (scenarios). This scenario-aware dataflow model uses a probabilistic approach to express the order in which scenarios (and different execution times within a scenario) occur. This paper discusses a tool for exhaustive and simulation-based analysis of various important performance metrics for scenario-aware streaming applications.