TIME-PREDICTABLE EXECUTION OF EMBEDDED SOFTWARE ON MULTI-CORE PLATFORMS

Ph.DDOCTOR OF PHILOSOPH

On static execution-time analysis

Proving timeliness is an integral part of the verification of safety-critical real-time systems. To this end, timing analysis computes upper bounds on the execution times of programs that execute on a given hardware platform. Modern hardware platforms commonly exhibit counter-intuitive timing behaviour: a locally slower execution can lead to a faster overall execution. Such behaviour challenges efficient timing analysis. In this work, we present and discuss a hardware design, the strictly in-order pipeline, that behaves monotonically w.r.t. the progress of a program's execution. Based on monotonicity, we prove the absence of the aforementioned counter-intuitive behaviour. At least since multi-core processors have emerged, timing analysis separates concerns by analysing different aspects of the system's timing behaviour individually. In this work, we validate the underlying assumption that a timing bound can be soundly composed from individual contributions. We show that even simple processors exhibit counter-intuitive behaviour - a locally slow execution can lead to an even slower overall execution - that impedes the soundness of the composition. We present the compositional base bound analysis that accounts for any such amplifying effects within its timing contribution. This enables a sound compositional analysis even for complex processors. Furthermore, we discuss hardware modifications that enable efficient compositional analyses.Echtzeitsysteme müssen unter allen Umständen beweisbar pünktlich arbeiten. Zum Beweis errechnet die Zeitanalyse obere Schranken der für die Ausführung von Programmen auf einer Hardware-Plattform benötigten Zeit. Moderne Hardware-Plattformen sind bekannt für unerwartetes Zeitverhalten bei dem eine lokale Verzögerung in einer global schnelleren Ausführung resultiert. Solches Zeitverhalten erschwert eine effiziente Analyse. Im Rahmen dieser Arbeit diskutieren wir das Design eines Prozessors mit eingeschränkter Fließbandverarbeitung (strictly in-order pipeline), der sich bzgl. des Fortschritts einer Programmausführung monoton verhält. Wir beweisen, dass Monotonie das oben genannte unerwartete Zeitverhalten verhindert. Spätestens seit dem Einsatz von Mehrkernprozessoren besteht die Zeitanalyse aus einzelnen Teilanalysen welche nur bestimmte Aspekte des Zeitverhaltens betrachten. Eine zentrale Annahme ist hierbei, dass sich die Teilergebnisse zu einer korrekten Zeitschranke zusammensetzen lassen. Im Rahmen dieser Arbeit zeigen wir, dass diese Annahme selbst für einfache Prozessoren ungültig ist, da eine lokale Verzögerung zu einer noch größeren globalen Verzögerung führen kann. Für bestehende Prozessoren entwickeln wir eine neuartige Teilanalyse, die solche verstärkenden Effekte berücksichtigt und somit eine korrekte Komposition von Teilergebnissen erlaubt. Für zukünftige Prozessoren beschreiben wir Modifikationen, die eine deutlich effizientere Zeitanalyse ermöglichen

Instruction and data cache modeling for timing analysis in real-time systems

Master'sMASTER OF ENGINEERIN

Enabling caches in probabilistic timing analysis

Hardware and software complexity of future critical real-time systems challenges the scalability of traditional timing analysis methods. Measurement-Based Probabilistic Timing Analysis (MBPTA) has recently emerged as an industrially-viable alternative technique to deal with complex hardware/software. Yet, MBPTA requires certain timing properties in the system under analysis that are not satisfied in conventional systems. In this thesis, we introduce, for the first time, hardware and software solutions to satisfy those requirements as well as to improve MBPTA applicability. We focus on one of the hardware resources with highest impact on both average performance and Worst-Case Execution Time (WCET) in current real-time platforms, the cache. In this line, the contributions of this thesis follow three different axes: hardware solutions and software solutions to enable MBPTA, and MBPTA analysis enhancements in systems featuring caches. At hardware level, we set the foundations of MBPTA-compliant processor designs, and define efficient time-randomised cache designs for single- and multi-level hierarchies of arbitrary complexity, including unified caches, which can be time-analysed for the first time. We propose three new software randomisation approaches (one dynamic and two static variants) to control, in an MBPTA-compliant manner, the cache jitter in Commercial off-the-shelf (COTS) processors in real-time systems. To that end, all variants randomly vary the location of programs' code and data in memory across runs, to achieve probabilistic timing properties similar to those achieved with customised hardware cache designs. We propose a novel method to estimate the WCET of a program using MBPTA, without requiring the end-user to identify worst-case paths and inputs, improving its applicability in industry. We also introduce Probabilistic Timing Composability, which allows Integrated Systems to reduce their WCET in the presence of time-randomised caches. With the above contributions, this thesis pushes the limits in the use of complex real-time embedded processor designs equipped with caches and paves the way towards the industrialisation of MBPTA technology.La complejidad de hardware y software de los sistemas críticos del futuro desafía la escalabilidad de los métodos tradicionales de análisis temporal. El análisis temporal probabilístico basado en medidas (MBPTA) ha aparecido últimamente como una solución viable alternativa para la industria, para manejar hardware/software complejo. Sin embargo, MBPTA requiere ciertas propiedades de tiempo en el sistema bajo análisis que no satisfacen los sistemas convencionales. En esta tesis introducimos, por primera vez, soluciones hardware y software para satisfacer estos requisitos como también mejorar la aplicabilidad de MBPTA. Nos centramos en uno de los recursos hardware con el máximo impacto en el rendimiento medio y el peor caso del tiempo de ejecución (WCET) en plataformas actuales de tiempo real, la cache. En esta línea, las contribuciones de esta tesis siguen 3 ejes distintos: soluciones hardware y soluciones software para habilitar MBPTA, y mejoras de el análisis MBPTA en sistemas usado caches. A nivel de hardware, creamos las bases del diseño de un procesador compatible con MBPTA, y definimos diseños de cache con tiempo aleatorio para jerarquías de memoria con uno y múltiples niveles de cualquier complejidad, incluso caches unificadas, las cuales pueden ser analizadas temporalmente por primera vez. Proponemos tres nuevos enfoques de aleatorización de software (uno dinámico y dos variedades estáticas) para manejar, en una manera compatible con MBPTA, la variabilidad del tiempo (jitter) de la cache en procesadores comerciales comunes en el mercado (COTS) en sistemas de tiempo real. Por eso, todas nuestras propuestas varían aleatoriamente la posición del código y de los datos del programa en la memoria entre ejecuciones del mismo, para conseguir propiedades de tiempo aleatorias, similares a las logradas con diseños hardware personalizados. Proponemos un nuevo método para estimar el WCET de un programa usando MBPTA, sin requerir que el usuario dentifique los caminos y las entradas de programa del peor caso, mejorando así la aplicabilidad de MBPTA en la industria. Además, introducimos la composabilidad de tiempo probabilística, que permite a los sistemas integrados reducir su WCET cuando usan caches de tiempo aleatorio. Con estas contribuciones, esta tesis empuja los limites en el uso de diseños complejos de procesadores empotrados en sistemas de tiempo real equipados con caches y prepara el terreno para la industrialización de la tecnología MBPTA

Effective memory management for mobile environments

Smartphones, tablets, and other mobile devices exhibit vastly different constraints compared to regular or classic computing environments like desktops, laptops, or servers. Mobile devices run dozens of so-called “apps” hosted by independent virtual machines (VM). All these VMs run concurrently and each VM deploys purely local heuristics to organize resources like memory, performance, and power. Such a design causes conflicts across all layers of the software stack, calling for the evaluation of VMs and the optimization techniques specific for mobile frameworks. In this dissertation, we study the design of managed runtime systems for mobile platforms. More specifically, we deepen the understanding of interactions between garbage collection (GC) and system layers. We develop tools to monitor the memory behavior of Android-based apps and to characterize GC performance, leading to the development of new techniques for memory management that address energy constraints, time performance, and responsiveness. We implement a GC-aware frequency scaling governor for Android devices. We also explore the tradeoffs of power and performance in vivo for a range of realistic GC variants, with established benchmarks and real applications running on Android virtual machines. We control for variation due to dynamic voltage and frequency scaling (DVFS), Just-in-time (JIT) compilation, and across established dimensions of heap memory size and concurrency. Finally, we provision GC as a global service that collects statistics from all running VMs and then makes an informed decision that optimizes across all them (and not just locally), and across all layers of the stack. Our evaluation illustrates the power of such a central coordination service and garbage collection mechanism in improving memory utilization, throughput, and adaptability to user activities. In fact, our techniques aim at a sweet spot, where total on-chip energy is reduced (20–30%) with minimal impact on throughput and responsiveness (5–10%). The simplicity and efficacy of our approach reaches well beyond the usual optimization techniques