Publication | Closed Access
Throughput Analysis of Synchronous Data Flow Graphs
264
Citations
21
References
2006
Year
Unknown Venue
Cluster ComputingThroughput AnalysisEngineeringComputer ArchitectureNetwork AnalysisSoftware EngineeringSoftware AnalysisSystems EngineeringParallel ComputingData ManagementThroughput RequirementsMassively-parallel ComputingData FlowComputer EngineeringComputer SciencePerformance Analysis ToolData-intensive ComputingGraph TheoryEdge ComputingProgram AnalysisParallel Performance EvaluationParallel ProgrammingData Flow Graph
Synchronous data flow graphs (SDFGs) are a useful tool for modeling and analyzing embedded data flow applications, both in a single processor and a multiprocessing context or for application mapping on platforms. Throughput analysis of these SDFGs is an important step for verifying throughput requirements of concurrent real-time applications, for instance within design-space exploration activities. Analysis of SDFGs can be hard, since the worst-case complexity of analysis algorithms is often high. This is also true for throughput analysis. In particular, many algorithms involve a conversion to another kind of data flow graph, the size of which can be exponentially larger than the size of the original graph. In this paper, we present a method for throughput analysis of SDFGs, based on explicit state-space exploration and we show that the method, despite its worst-case complexity, works well in practice, while existing methods often fail. We demonstrate this by comparing the method with state-of-the-art cycle mean computation algorithms. Moreover, since the state-space exploration method is essentially the same as simulation of the graph, the results of this paper can be easily obtained as a byproduct in existing simulation tools
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