{"title":"A unified framework for throughput analysis of synchronous data flow graphs under memory constraints: work-in-progress","authors":"Xue-Yang Zhu","doi":"10.1145/3125502.3125535","DOIUrl":null,"url":null,"abstract":"Streaming applications are often modeled with Synchronous data flow graphs (SDFGs). A proper analysis of the models is helpful to predict the performance of a system. In this paper, we focus on the throughput analysis of memory-constrained SDFGs (MC SDFGs), which needs to choose a memory abstraction that decides when the space of consumed data is released and when the required space is claimed. Different memory abstractions may lead to different achievable throughputs. The existing techniques, however, consider only a certain abstraction. If a model is implemented according to other abstractions, the analysis result may not truly evaluate the performance of the system. In this paper, we present a unified framework for throughput analysis of MC SDFGs for difference abstractions, aiming to provide evaluations matching up to the corresponding implementations.","PeriodicalId":350509,"journal":{"name":"Proceedings of the Twelfth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis Companion","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Twelfth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis Companion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3125502.3125535","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
Streaming applications are often modeled with Synchronous data flow graphs (SDFGs). A proper analysis of the models is helpful to predict the performance of a system. In this paper, we focus on the throughput analysis of memory-constrained SDFGs (MC SDFGs), which needs to choose a memory abstraction that decides when the space of consumed data is released and when the required space is claimed. Different memory abstractions may lead to different achievable throughputs. The existing techniques, however, consider only a certain abstraction. If a model is implemented according to other abstractions, the analysis result may not truly evaluate the performance of the system. In this paper, we present a unified framework for throughput analysis of MC SDFGs for difference abstractions, aiming to provide evaluations matching up to the corresponding implementations.