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Predicting timing behavior is key to reliable real-time system design and verification, but becomes increasingly difficult for current multiprocessor systems on chip. The integration of formerly separate functionality into a single multicore system introduces new intercore timing dependencies resulting from the common use of the now shared resources. This feedback of system timing on local timing makes traditional performance analysis approaches inappropriate. This article presents a general methodology to model the shared resource traffic and consider its effect on the local task execution. The aggregate busy time captures the timing of multiple accesses to a shared memory far better than the traditional models that focus on the timing of individual events. An iterative approach is proposed to tackle the analysis dependencies that exist in systems with event-driven task activation and dynamic resource arbitration.

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System level performance analysis plays a fundamental role in the design process of real-time embedded systems. Several different approaches have been presented so far to address the problem of accurate performance analysis of distributed embedded systems in early design stages. The existing formal analysis methods are based on essentially different concepts of abstraction. However, the influence of these different models on the accuracy of the system analysis is widely unknown, as a direct comparison of performance analysis methods has not been considered so far. We define a set of benchmarks aimed at the evaluation of performance analysis techniques for distributed systems. We apply different analysis methods to the benchmarks and compare the results obtained in terms of accuracy and analysis times, highlighting the specific effects of the various abstractions. We also point out several pitfalls for the analysis accuracy of single approaches and investigate the reasons for pessimistic performance predictions.

System level performance analysis plays a fundamental role in the design process of hard real-time embedded systems. Several different approaches have been presented so far to address the problem of accurate performance analysis of distributed embedded systems in early design stages. The existing formal analysis methods are based on essentially different concepts of abstraction. However, the influence of these different models on the accuracy of the system analysis is widely unknown, as a direct comparison of performance analysis methods has not been considered so far. We define a set of benchmarks aimed at the 28 S. Perathoner et al. evaluation of performance analysis techniques for distributed systems. We apply different analysis methods to the benchmarks and compare the results obtained in terms of accuracy and analysis times, highlighting the specific effects of the various abstractions. We also point out several pitfalls for the analysis accuracy of single approaches and investigate the reasons for pessimistic performance predictions.

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