1,205 research outputs found
Randomized Caches Can Be Pretty Useful to Hard Real-Time Systems
Cache randomization per se, and its viability for probabilistic timing analysis (PTA) of critical real-time systems, are receiving increasingly close attention from the scientific community and the industrial practitioners. In fact, the very notion of introducing randomness and probabilities in time-critical systems has caused strenuous debates owing to the apparent clash that this idea has with the strictly deterministic view traditionally held for those systems. A paper recently appeared in LITES (Reineke, J. (2014). Randomized Caches Considered Harmful in Hard Real-Time Systems. LITES, 1(1), 03:1-03:13.) provides a critical analysis of the weaknesses and risks entailed in using randomized caches in hard real-time systems. In order to provide the interested reader with a fuller, balanced appreciation of the subject matter, a critical analysis of the benefits brought about by that innovation should be provided also. This short paper addresses that need by revisiting the array of issues addressed in the cited work, in the light of the latest advances to the relevant state of the art. Accordingly, we show that the potential benefits of randomized caches do offset their limitations, causing them to be - when used in conjunction with PTA - a serious competitor to conventional designs
A confidence assessment of WCET estimates for software time randomized caches
Obtaining Worst-Case Execution Time (WCET) estimates is a required step in real-time embedded systems during software verification. Measurement-Based Probabilistic Timing Analysis (MBPTA) aims at obtaining WCET estimates for industrial-size software running upon hardware platforms comprising high-performance features. MBPTA relies on the randomization of timing behavior (functional behavior is left unchanged) of hard-to-predict events like the location of objects in memory — and hence their associated cache behavior — that significantly impact software's WCET estimates. Software time-randomized caches (sTRc) have been recently proposed to enable MBPTA on top of Commercial off-the-shelf (COTS) caches (e.g. modulo placement). However, some random events may challenge MBPTA reliability on top of sTRc. In this paper, for sTRc and programs with homogeneously accessed addresses, we determine whether the number of observations taken at analysis, as part of the normal MBPTA application process, captures the cache events significantly impacting execution time and WCET. If this is not the case, our techniques provide the user with the number of extra runs to perform to guarantee that cache events are captured for a reliable application of MBPTA. Our techniques are evaluated with synthetic benchmarks and an avionics application.The research leading to these results has received funding from the European Community’s Seventh Framework Programme [FP7/2007-2013] under the PROXIMA Project
(www.proxima-project.eu), grant agreement no 611085. This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316, the HiPEAC Network of Excellence, and COST Action IC1202: Timing Analysis On Code-Level (TACLe). Jaume Abella has been partially supported by the Ministry of Economy and
Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717.Peer ReviewedPostprint (author's final draft
Random Modulo: A new processor cache design for real-time critical systems
Cache memories have a huge impact on software's worst-case execution time (WCET). While enabling the seamless use of caches is key to provide the increasing levels of (guaranteed) performance required by automotive software, caches complicate timing analysis. In the context of Measurement-Based Probabilistic Timing Analysis (MBPTA) - a promising technique to ease timing analyis of complex hardware - we propose Random Modulo (RM), a new cache design that provides the probabilistic behavior required by MBPTA and with the following advantages over existing MBPTA-compliant cache designs: (i) an outstanding reduction in WCET estimates, (ii) lower latency and area overhead, and (iii) competitive average performance w.r.t conventional caches.Peer ReviewedPostprint (author's final draft
Resilient random modulo cache memories for probabilistically-analyzable real-time systems
Fault tolerance has often been assessed separately in safety-related real-time systems, which may lead to inefficient solutions. Recently, Measurement-Based Probabilistic Timing Analysis (MBPTA) has been proposed to estimate Worst-Case Execution Time (WCET) on high performance hardware. The intrinsic probabilistic nature of MBPTA-commpliant hardware matches perfectly with the random nature of hardware faults.
Joint WCET analysis and reliability assessment has been done so far for some MBPTA-compliant designs, but not for the most promising cache design: random modulo. In this paper we perform, for the first time, an assessment of the aging-robustness of random modulo and propose new implementations preserving the key properties of random modulo, a.k.a. low critical path impact, low miss rates and MBPTA compliance, while enhancing reliability in front of aging by achieving a better – yet random – activity distribution across cache sets.Peer ReviewedPostprint (author's final draft
Modelling probabilistic cache representativeness in the presence of arbitrary access patterns
Measurement-Based Probabilistic Timing Analysis (MBPTA) is a promising powerful industry-friendly method to derive worst-case execution time (WCET) estimates as needed for critical real-time embedded systems. MBPTA performs several (R) runs of the program on the target platform collecting the execution times in each run. MBPTA builds a probabilistic representativeness argument on whether those events with high impact on execution time, such as cache misses, arise on the runs made at analysis time so that their impact on execution time is captured. So far only events occurring in cache memories have been shown to challenge providing such representativeness argument.
In this context, this paper introduces a representativeness validation method (RVS) to assess the probabilistic representativeness of MBPTA’s execution time observations in terms of cache behaviour. RVS resorts to cache simulation to predict worst-case miss scenarios that can appear during the
deployment phase. RVS also constructs a probabilistic Worst-Case Miss Count curve based on the miss-counts captured in the R runs. If that curve upperbounds the impact of the predicted cache worst-case scenarios, R is deemed as a sufficient number of runs for which pWCET estimates can be reliably derived. Otherwise, the user is requested to perform more runs until all cache scenarios of interest are captured.Peer ReviewedPostprint (author's final draft
pTNoC: Probabilistically time-analyzable tree-based NoC for mixed-criticality systems
The use of networks-on-chip (NoC) in real-time safety-critical multicore systems challenges deriving tight worst-case execution time (WCET) estimates. This is due to the complexities in tightly upper-bounding the contention in the access to the NoC among running tasks. Probabilistic Timing Analysis (PTA) is a powerful approach to derive WCET estimates on relatively complex processors. However, so far it has only been tested on small multicores comprising an on-chip bus as communication means, which intrinsically does not scale to high core counts. In this paper we propose pTNoC, a new tree-based NoC design compatible with PTA requirements and delivering scalability towards medium/large core counts. pTNoC provides tight WCET estimates by means of asymmetric bandwidth guarantees for mixed-criticality systems with negligible impact on average performance. Finally, our implementation results show the reduced area and power costs of the pTNoC.The research leading to these results has received funding from the European Community’s Seventh Framework Programme [FP7/2007-2013] under the PROXIMA Project
(www.proxima-project.eu), grant agreement no 611085. This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Mladen Slijepcevic is funded by the Obra Social Fundación la Caixa under grant Doctorado “la Caixa” - Severo Ochoa. 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.Peer ReviewedPostprint (author's final draft
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
Measurement-Based Timing Analysis of the AURIX Caches
Cache memories are one of the hardware resources with higher potential to reduce worst-case execution time (WCET) costs for software programs with tight real-time constraints. Yet, the complexity of cache analysis has caused a large fraction of real-time systems industry to avoid using them, especially in the automotive sector. For measurement-based timing analysis (MBTA) - the dominant technique in domains such as automotive - cache challenges the definition of test scenarios stressful enough to produce (cache) layouts that causing high contention.
In this paper, we present our experience in enabling the use of caches for a real automotive application running on an AURIX multiprocessor, using software randomization and measurement-based probabilistic timing analysis (MBPTA). Our results show that software randomization successfully exposes - in the experiments performed for timing analysis - cache related variability, in a manner that can be effectively captured by MBPTA
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