Re-sampling for statistical timing analysis of real-time systems
Proceedings of the 20th International Conference on Real-Time and Network Systems
Kernel Partitioning of Streaming Applications: A Statistical Approach to an NP-complete Problem
MICRO-45 Proceedings of the 2012 45th Annual IEEE/ACM International Symposium on Microarchitecture
On the convergence of mainstream and mission-critical markets
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Thermal analysis of periodic real-time systems with stochastic properties: an analytical approach
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ACM SIGBED Review - Special Issue on the 3rd Embedded Operating System Workshop (EWiLi 2013)
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The rigorous application of static timing analysis requires a large and costly amount of detail knowledge on the hardware and software components of the system. Probabilistic Timing Analysis has potential for reducing the weight of that demand. In this paper, we present a sound measurement-based probabilistic timing analysis technique based on Extreme Value Theory. In all the experiments made as part of this work, the timing bounds determined by our technique were less than 15% pessimistic in comparison with the tightest possible bounds obtainable with any probabilistic timing analysis technique. As a point of interest to industrial users, our technique also requires a comparatively low number of measurement runs of the program under analysis, less than 650 runs were needed for the benchmarks presented in this paper.