Software timing analysis for complex hardware with survivability and risk analysis
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
European Commission's projectSuPerCom - Sustainable Performance for High-Performance Embedded Computing Systems (EC-H2020-772773)
The increasing automation of safety-critical real-time systems, such as those in cars and planes, leads, to more complex and performance-demanding on-board software and the subsequent adoption of multicores and accelerators. This causes software's execution time dispersion to increase due to variable-latency resources such as caches, NoCs, advanced memory controllers and the like. Statistical analysis has been proposed to model the Worst-Case Execution Time (WCET) of software running such complex systems by providing reliable probabilistic WCET (pWCET) estimates. However, statistical models used so far, which are based on risk analysis, are overly pessimistic by construction. In this paper we prove that statistical survivability and risk analyses are equivalent in terms of tail analysis and, building upon survivability analysis theory, we show that Weibull tail models can be used to estimate pWCET distributions reliably and tightly. In particular, our methodology proves the correctness-by-construction of the approach, and our evaluation provides evidence about the tightness of the pWCET estimates obtained, which allow decreasing them reliably by 40% for a railway case study w.r.t. state-of-the-art exponential tails.
CitationVilardell, S. [et al.]. Software timing analysis for complex hardware with survivability and risk analysis. A: IEEE International Conference on Computer Design. "2019 IEEE International Conference on Computer Design, ICCD 2019: Abu Dhabi, UAE 17-20 November 2019: proceeding". Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 227-236.
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