Formale Methoden zur Systemperformanzanalyse und -optimierung

With increasing system complexity, there is growing interest in using formal methods in wider range of systems to improve system predictability and determine system robustness to changes, enhancements and pitfalls. This paper gives an overview over a formal approach to system level performance modelling and analysis. A methodology is presented to cover distributed multiprocessor systems as well as multiprocessor systems on chip. The abstract modelling allows early design space exploration and optimization. We investigate an example multimedia application and optimize the usage of the shared memory to reach an optimal performance

Influence of different abstractions on the performance analysis of distributed hard real-time systems

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 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 prediction

Determining Accurate Output Event Models To Improve System Performance Estimation

Recent approaches to heterogeneous system analysis combine local scheduling analysis techniques with event stream propagation. The techniques assume the availability of output event stream models, so far, widely neglected in scheduling analysis. This paper shows how to derive such models for two popular scheduling algorithms and a wide range of task configurations and input conditions. In particular

A formal approach to multi-dimensional sensitivity analysis of embedded realtime systems

System robustness is a major concern in the design of efficient and reliable state-of-the-art heterogenous embedded real-time systems. Due to complex component interactions, resource sharing and functional dependencies, one-dimensional sensitivity analysis cannot cover all effects that modifications of one system property may have on system performance. One reason is that the variation of one property can also affect the values of other system properties requiring new approaches to keep track of simultaneous parameter changes. In this paper we present a heuristic and a stochastic approach suited for the multi-dimensional sensitivity analysis of large heterogenous embedded systems with complex timing constraints.

Formal Methods for Automotive Platform Analysis and Optimization

There have been major advances in formal methods and related tools in embedded system design in recent years that support analysis and optimization of heterogeneous automotive architectures. We give an introduction of the tool SymTA/S and demonstrate its application to an automotive example where we analyze system sensitivity and explore the design space. Such results cannot be obtained by simulation or prototyping

Calculating Task Output Event Models to Reduce Distributed System Cost

Input event models such as periodic, jitter, and sporadic are known as powerful abstractions for task workload arrival in scheduling analysis. In distributed systems, such task input models result from output event models of other tasks in the system. Interestingly, output event models have received only little attention in literature. In this paper, we introduce a novel approach to determine task output event models for the most practically important task configurations. We show that the output event model accuracy is key to efficient system dimensioning with a direct impact on system cost, and we propose several optimizations. The experiments show that the new approach reveals previously unknown, and hence, unexploited system performance reserves

Applying Sensitivity Analysis in Real-Time Distributed Systems

During real-world design of embedded real-time systems, it cannot be expected that all performance data required for scheduling analysis is fully available up front. In such situations, sensitivity analysis is a promising approach to deal with uncertainties that result from incomplete specifications, early performance estimates, late feature requests, and so on. Sensitivity analysis allows the system designer to keep track of the flexibility of the system, and thus to quickly assess the impact of changes of individual hardware and software components on system performance. In this paper we integrate sensitivity analysis into our system-level performance analysis framework SymTA/S and show its benefits during the design of complex, networked multi-processor embedded real-time systems