{"title":"System-level power/performance analysis for embedded systems design","authors":"A. Nandi, R. Marculescu","doi":"10.1145/378239.379032","DOIUrl":null,"url":null,"abstract":"This paper presents a formal technique for system-level power/performance analysis that can help the designer to select the right platform starting from a set of target applications. By platform we mean a family of heterogeneous architectures that satisfy a set of architectural constraints imposed to allow re-use of hardware and software components. More precisely, we introduce the Stochastic Automata Networks (SANs) as an effective formalism for average-case analysis that can be used early in the design cycle to identify the best power/performance figure among several application-architecture combinations. This information not only helps avoid lengthy profiling simulations, but also enables efficiency mappings of the applications onto the chosen platform. We illustrate the features of our technique through the design of an MPEG-2 video decoder application.","PeriodicalId":154316,"journal":{"name":"Proceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"63","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/378239.379032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 63
Abstract
This paper presents a formal technique for system-level power/performance analysis that can help the designer to select the right platform starting from a set of target applications. By platform we mean a family of heterogeneous architectures that satisfy a set of architectural constraints imposed to allow re-use of hardware and software components. More precisely, we introduce the Stochastic Automata Networks (SANs) as an effective formalism for average-case analysis that can be used early in the design cycle to identify the best power/performance figure among several application-architecture combinations. This information not only helps avoid lengthy profiling simulations, but also enables efficiency mappings of the applications onto the chosen platform. We illustrate the features of our technique through the design of an MPEG-2 video decoder application.
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