PROARTIS: Probabilistically analyzable real-time systems

Static timing analysis is the state-of-the-art practice of ascertaining the timing behavior of currentgeneration real-time embedded systems. The adoption of more complex hardware to respond to the increasing demand for computing power in next-generation systems exacerbates some of the limitations of static timing analysis. In particular, the effort of acquiring (1) detailed information on the hardware to develop an accurate model of its execution latency as well as (2) knowledge of the timing behavior of the program in the presence of varying hardware conditions, such as those dependent on the history of previously executed instructions. We call these problems the timing analysis walls. In this vision-statement article, we present probabilistic timing analysis, a novel approach to the analysis of the timing behavior of next-generation real-time embedded systems. We show how probabilistic timing analysis attacks the timing analysis walls; we then illustrate the mathematical foundations on which this method is based and the challenges we face in the effort of efficiently implementing it. We also present experimental evidence that shows how probabilistic timing analysis reduces the extent of knowledge about the execution platform required to produce probabilistically accurate WCET estimations. © 2013 ACM.Peer Reviewe

PROARTIS

none14Static Timing Analysis is the state-of-the-art practice to ascertain the timing behaviour of current-generation real-time embedded systems. The adoption of more complex hardware to respond to the increasing demand for computing power in next-generation systems exacerbates some of the limitations of Static Timing Analysis. In particular, the effort of acquiring (1) detail information on the hardware to develop an accurate model of its execution latency as well as (2) knowledge of the timing behaviour of the program in the presence of varying hardware conditions, such as those dependent on the history of previously executed instructions. We call these problems the Timing Analysis Walls. In this vision-statement paper we present Probabilistic Timing Analysis, a novel approach to the analysis of the timing behaviour of next-generation real-time embedded systems. We show how Probabilistic Timing Analysis attacks the Timing Analysis Walls; we then illustrate the mathematical foundations on which this method is based and the challenges we face in the effort of efficiently implementing it. We also present experimental evidence that shows how Probabilistic Timing Analysis reduces the extent of knowledge about the execution platform required to produce probabilistically-safe and tight WCET estimations.noneFrancisco J. Cazorla;Michael Houston;Luca Santinelli;Leonidas Kosmidis;Code Lo;Dorin Maxim;Eduardo Quiñones;Tullio Vardanega;Liliana Cucu;Benoit Triquet;Guillem Bernat;Emery Berger;Jaume Abella;Franck WartelFrancisco J., Cazorla; Michael, Houston; Luca, Santinelli; Leonidas, Kosmidis; Code, Lo; Dorin, Maxim; Eduardo, Quiñones; Vardanega, Tullio; Liliana, Cucu; Benoit, Triquet; Guillem, Bernat; Emery, Berger; Jaume, Abella; Franck, Warte

PROARTIS: Probabilistically Analyzable Real-Time System

International audienceStatic timing analysis is the state-of-the-art practice of ascertaining the timing behavior of current-generation real-time embedded systems. The adoption of more complex hardware to respond to the increasing demand for computing power in next-generation systems exacerbates some of the limitations of static timing analysis. In particular, the effort of acquiring (1) detailed information on the hardware to develop an accurate model of its execution latency as well as (2) knowledge of the timing behavior of the program in the presence of varying hardware conditions, such as those dependent on the history of previously executed instructions. We call these problems the timing analysis walls. In this vision-statement article, we present probabilistic timing analysis, a novel approach to the analysis of the timing behavior of next-generation real-time embedded systems. We show how probabilistic timing analysis attacks the timing analysis walls; we then illustrate the mathematical foundations on which this method is based and the challenges we face in the effort of efficiently implementing it. We also present experimental evidence that shows how probabilistic timing analysis reduces the extent of knowledge about the execution platform required to produce probabilistically accurate WCET estimations