2003Unpublished venueRequires access

WCET analysis of probabilistic hard real-time systems

Guillem Bernat, A. Colin, Stefan M. Petters

Open publisher page 338 citations

Abstract

Traditional approaches for worst case execution time (WCET) analysis produce values which are very pessimistic if applied to modern processors. In addition, end to end measurements as used in industry produce estimates of the execution time that potentially underestimate the real worst case execution time. We introduce the notion of probabilistic hard real-time systems which have to meet all the deadlines but for which a (high) probabilistic guarantee suffices. We combine both measurement and analytical approaches into a model for computing probabilistically bounds on the execution time of the worst case path of sections of code. The idea of the technique presented is based on combining (probabilistically) the worst case effects seen in individual blocks to build the execution time model of the worst case path of the program (such case may have not been observed in the measurements). We provide three alternative operators for the combination based on whether the information of their dependency is known. Experimental evaluation of a two case study shows extremely low probabilities of the values obtained by traditional analysis.

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What this paper is about

Traditional approaches for worst case execution time (WCET) analysis produce values which are very pessimistic if applied to modern processors. In addition, end to end measurements as used in industry produce estimates of the execution time that potentially underestimate the real worst case execution time. We introduce the notion of probabilistic hard real-time systems which have to meet all the deadlines but for which a (high) probabilistic guarantee suffices. We combine both measurement and analytical approaches into a model for computing probabilistically bounds on the execution time of the worst case path of sections of code. The idea of the technique presented is based on combining (probabilistically) the worst case effects seen in individual blocks to build the execution time model of the worst case path of the program (such case may have not been observed in the measurements). We provide three alternative operators for the combination based on whether the information of their dependency is known. Experimental evaluation of a two case study shows extremely low probabilities of the values obtained by traditional analysis.

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Available abstract

Traditional approaches for worst case execution time (WCET) analysis produce values which are very pessimistic if applied to modern processors. In addition, end to end measurements as used in industry produce estimates of the execution time that potentially underestimate the real worst case execution time. We introduce the notion of probabilistic hard real-time systems which have to meet all the deadlines but for which a (high) probabilistic guarantee suffices. We combine both measurement and analytical approaches into a model for computing probabilistically bounds on the execution time of the worst case path of sections of code. The idea of the technique presented is based on combining (probabilistically) the worst case effects seen in individual blocks to build the execution time model of the worst case path of the program (such case may have not been observed in the measurements). We provide three alternative operators for the combination based on whether the information of their dependency is known. Experimental evaluation of a two case study shows extremely low probabilities of the values obtained by traditional analysis.

Key concepts: Worst-case execution time, Computer science, Probabilistic logic, Execution time, Dependency (UML), Path (computing), Code (set theory), Probabilistic analysis of algorithms

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