Embedded systems are becoming ubiquitous and are subject to demanding standards in both safety and reliability. Modern vehicles, which must respect ISO 26262 standards, use up to 100 Electronic Control Unit (ECUs). Advances in microelectronics enable integration of more functions in the ECU, but at the cost of greater unreliability in hostile operating environments, such as electromagnetic fields, temperature, and humidity. Their software mainly drives embedded system flexibility and smartness. However due to lack of automation, its validation and verification (V&V) takes place throughout the design process and tends to swallow up 40% to 50% of the total development cost. The “Enhanced Quality Using Intensive Test Analysis on Simulators” (EQUITAS) project intends to limit the impact of software V&V on embedded systems cost and time-to-market while improving reliability and functional safety. Project activities include: development of a continuous tool-chain to automate the V&V process of embedded computers, improving the relevance of the test campaigns by detecting the redundant tests using equivalence classes, providing assistance for hardware failure effect analysis (FMEA), and finally assessing the tool-chain under the ISO 26262 requirements.

SystemC is rapidly gaining wide acceptance as a simulation framework for SoC and embedded processors. While its main assets are modularity and the very fact it is becoming a de facto standard, the evolution of the SystemC framework (from version 0.9 to version 2.0.1) suggests the environment is particularly geared toward increasing the framework functionalities rather than improving simulation speed. For cycle-level simulation, speed is a critical factor as simulation can be extremely slow, affecting the extent of design space exploration. In this article, we present a fast SystemC engine that, in our experience, can speed up simulations by a factor of 1.93 to 3.56 over SystemC 2.0.1. This SystemC engine is designed for cycle-level simulators and for the moment, it only supports the subset of the SystemC syntax (signals, methods) that is most often used for such simulators. We achieved greater speed (1) by completely rewriting the SystemC engine and improving the implementation software engineering, and (2) by proposing a new scheduling technique, intermediate between SystemC dynamic scheduling technique and existing static scheduling schemes. Unlike SystemC dynamic scheduling, our technique removes many if not all useless process wake-ups, while using a simpler scheduling algorithm than in existing static scheduling techniques.

While most research papers on computer architectures include some performance measurements, these performance numbers tend to be distrusted. Up to the point that, after so many research articles on data cache architectures, for instance, few researchers have a clear view of what are the best data cache mechanisms. To illustrate the usefulness of a fair quantitative comparison, we have picked a target architecture component for which lots of optimizations have been proposed (data caches), and we have implemented most of the performance-oriented hardware data cache optimizations published in top conferences in the past 4 years. Beyond the comparison of data cache ideas, our goals are twofold: (1) to clearly and quantitatively evaluate the effect of methodology shortcomings, such as model precision, benchmark selection, trace selection..., on assessing and comparing research ideas, and to outline how strong is the methodology effect in many cases, (2) to outline that the lack of interoperable simulators and not disclosing simulators at publication time make it difficult if not impossible to fairly assess the benefit of research ideas. This study is part of a broader effort, called MicroLib, an open library of modular simulators aimed at promoting the disclosure and sharing of simulator models.

While architecture simulation is often treated as a methodology issue, it is at the core of most processor architecture research works, and simulation speed is often the bottleneck of the typical trial-and-error research process. To speedup simulation during this research process and get trends faster, researchers usually reduce the trace size. More sophisticated techniques like trace sampling or distributed simulation are scarcely used because they are considered unreliable and complex due to their impact on accuracy and the associated warm-up issues.In this article, we present DiST, a practical distributed simulation scheme where, unlike in other simulation techniques that trade accuracy for speed, the user is relieved from most accuracy issues thanks to an automatic and dynamic mechanism for adjusting the warm-up interval size. Moreover, the mechanism is designed so as to always privilege accuracy over speedup. The speedup scales with the amount of available computing resources, bringing an average 7.35 speedup on 10 machines with an average IPC error of 1.81% and a maximum IPC error of 5.06%.Besides proposing a solution to the warm-up issues in distributed simulation, we experimentally show that our technique is significantly more accurate than trace size reduction or trace sampling for identical speedups. We also show that not only the error always remains small for IPC and other metrics, but that a researcher can reliably base research decisions on DiST simulation results. Finally, we explain how the DiST tool is designed to be easily pluggable into existing architecture simulators with very few modifications.