Probabilistic Worst-Case Timing Analysis: Taxonomy and Comprehensive Survey

"© ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Computing Surveys, {VOL 52, ISS 1, (February 2019)} https://dl.acm.org/doi/10.1145/3301283"[EN] The unabated increase in the complexity of the hardware and software components of modern embedded real-time systems has given momentum to a host of research in the use of probabilistic and statistical techniques for timing analysis. In the last few years, that front of investigation has yielded a body of scientific literature vast enough to warrant some comprehensive taxonomy of motivations, strategies of application, and directions of research. This survey addresses this very need, singling out the principal techniques in the state of the art of timing analysis that employ probabilistic reasoning at some level, building a taxonomy of them, discussing their relative merit and limitations, and the relations among them. In addition to offering a comprehensive foundation to savvy probabilistic timing analysis, this article also identifies the key challenges to be addressed to consolidate the scientific soundness and industrial viability of this emerging field.This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P, the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 772773), and the HiPEAC Network of Excellence. Jaume Abella was partially supported by the Ministry of Economy and Competitiveness under a Ramon y Cajal postdoctoral fellowship (RYC-2013-14717). Enrico Mezzetti has been partially supported by the Spanish Ministry of Economy and Competitiveness under Juan de la Cierva-Incorporación postdoctoral fellowship No. IJCI-2016-27396.Cazorla, FJ.; Kosmidis, L.; Mezzetti, E.; Hernández Luz, C.; Abella, J.; Vardanega, T. (2019). Probabilistic Worst-Case Timing Analysis: Taxonomy and Comprehensive Survey. ACM Computing Surveys. 52(1):1-35. https://doi.org/10.1145/3301283S13552

Modeling RTL Fault Models Behavior to Increase the Confidence on TSIM-based Fault Injection

Future high-performance safety-relevant applications require microcontrollers delivering higher performance than the existing certified ones. However, means for assessing their dependability are needed so that they can be certified against safety critical certification standars (e.g ISO26262). Dependability assessment analyses performed at high level of abstraction inject single faults to investigate the effects these have in the system. In this work we show that single faults do not comprise the whole picture, due to fault multiplicities and reactivations. Later we prove that, by injecting complex fault models that consider multiplicities and reactivations in higher levels of abstraction, results are substantially different, thus indicating that a change in the methodology is needed.The research leading to these results has received funding from the Ministry of Science and Technology of Spain under contract TIN2015-65316-P and the HiPEAC Network of Excellence. Carles Hern´andez is jointly funded by the Spanish Ministry of Economy and Competitiveness (MINECO) and FEDER funds through grant TIN2014-60404-JIN. Jaume Abella has been partially supported by the MINECO under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717.Postprint (author's final draft

DeSyRe: on-Demand System Reliability

The DeSyRe project builds on-demand adaptive and reliable Systems-on-Chips (SoCs). As fabrication technology scales down, chips are becoming less reliable, thereby incurring increased power and performance costs for fault tolerance. To make matters worse, power density is becoming a significant limiting factor in SoC design, in general. In the face of such changes in the technological landscape, current solutions for fault tolerance are expected to introduce excessive overheads in future systems. Moreover, attempting to design and manufacture a totally defect and fault-free system, would impact heavily, even prohibitively, the design, manufacturing, and testing costs, as well as the system performance and power consumption. In this context, DeSyRe delivers a new generation of systems that are reliable by design at well-balanced power, performance, and design costs. In our attempt to reduce the overheads of fault-tolerance, only a small fraction of the chip is built to be fault-free. This fault-free part is then employed to manage the remaining fault-prone resources of the SoC. The DeSyRe framework is applied to two medical systems with high safety requirements (measured using the IEC 61508 functional safety standard) and tight power and performance constraints

Cross-layer reliability evaluation, moving from the hardware architecture to the system level: A CLERECO EU project overview

Advanced computing systems realized in forthcoming technologies hold the promise of a significant increase of computational capabilities. However, the same path that is leading technologies toward these remarkable achievements is also making electronic devices increasingly unreliable. Developing new methods to evaluate the reliability of these systems in an early design stage has the potential to save costs, produce optimized designs and have a positive impact on the product time-to-market. CLERECO European FP7 research project addresses early reliability evaluation with a cross-layer approach across different computing disciplines, across computing system layers and across computing market segments. The fundamental objective of the project is to investigate in depth a methodology to assess system reliability early in the design cycle of the future systems of the emerging computing continuum. This paper presents a general overview of the CLERECO project focusing on the main tools and models that are being developed that could be of interest for the research community and engineering practice

High performance fault tolerance through predictive instruction re-execution

Processor designers face the challenge of defect formation, leading to permanent faults, during fabrication and operation. Permanent or hard fault tolerance is an important problem in computing systems, solutions to which can help improve yield during fabrication and reduce the cost of transistor mortality during the service life of the processor. This paper presents PreFix, a method to handle hard errors to keep a faulty core running and correctly executing instructions. Instead of turning off faulty structures, PreFix predicts early on whether an instruction is likely to use faulty components, then refines this prediction later in the pipeline to actually detect when an error has occurred. Instructions marked as possibly- faulty in the front-end are queued for duplicate execution on a separate core. At commit, results from the original and duplicate instructions are compared. Upon a mismatch, the original instruction is patched up, the pipeline flushed and execution continues. Using PreFix, faulty components can continue performing useful work when their errors do not manifest in architecturally visible state changes. This enhances processor lifetime with minimal performance overhead