Energy Transparency for Deeply Embedded Programs

Energy transparency is a concept that makes a program's energy consumption visible, from hardware up to software, through the different system layers. Such transparency can enable energy optimizations at each layer and between layers, and help both programmers and operating systems make energy-aware decisions. In this paper, we focus on deeply embedded devices, typically used for Internet of Things (IoT) applications, and demonstrate how to enable energy transparency through existing Static Resource Analysis (SRA) techniques and a new target-agnostic profiling technique, without hardware energy measurements. Our novel mapping technique enables software energy consumption estimations at a higher level than the Instruction Set Architecture (ISA), namely the LLVM Intermediate Representation (IR) level, and therefore introduces energy transparency directly to the LLVM optimizer. We apply our energy estimation techniques to a comprehensive set of benchmarks, including single- and also multi-threaded embedded programs from two commonly used concurrency patterns, task farms and pipelines. Using SRA, our LLVM IR results demonstrate a high accuracy with a deviation in the range of 1% from the ISA SRA. Our profiling technique captures the actual energy consumption at the LLVM IR level with an average error of 3%.Comment: 33 pages, 7 figures. arXiv admin note: substantial text overlap with arXiv:1510.0709

A time-predictable many-core processor design for critical real-time embedded systems

Critical Real-Time Embedded Systems (CRTES) are in charge of controlling fundamental parts of embedded system, e.g. energy harvesting solar panels in satellites, steering and breaking in cars, or flight management systems in airplanes. To do so, CRTES require strong evidence of correct functional and timing behavior. The former guarantees that the system operates correctly in response of its inputs; the latter ensures that its operations are performed within a predefined time budget. CRTES aim at increasing the number and complexity of functions. Examples include the incorporation of \smarter" Advanced Driver Assistance System (ADAS) functionality in modern cars or advanced collision avoidance systems in Unmanned Aerial Vehicles (UAVs). All these new features, implemented in software, lead to an exponential growth in both performance requirements and software development complexity. Furthermore, there is a strong need to integrate multiple functions into the same computing platform to reduce the number of processing units, mass and space requirements, etc. Overall, there is a clear need to increase the computing power of current CRTES in order to support new sophisticated and complex functionality, and integrate multiple systems into a single platform. The use of multi- and many-core processor architectures is increasingly seen in the CRTES industry as the solution to cope with the performance demand and cost constraints of future CRTES. Many-cores supply higher performance by exploiting the parallelism of applications while providing a better performance per watt as cores are maintained simpler with respect to complex single-core processors. Moreover, the parallelization capabilities allow scheduling multiple functions into the same processor, maximizing the hardware utilization. However, the use of multi- and many-cores in CRTES also brings a number of challenges related to provide evidence about the correct operation of the system, especially in the timing domain. Hence, despite the advantages of many-cores and the fact that they are nowadays a reality in the embedded domain (e.g. Kalray MPPA, Freescale NXP P4080, TI Keystone II), their use in CRTES still requires finding efficient ways of providing reliable evidence about the correct operation of the system. This thesis investigates the use of many-core processors in CRTES as a means to satisfy performance demands of future complex applications while providing the necessary timing guarantees. To do so, this thesis contributes to advance the state-of-the-art towards the exploitation of parallel capabilities of many-cores in CRTES contributing in two different computing domains. From the hardware domain, this thesis proposes new many-core designs that enable deriving reliable and tight timing guarantees. From the software domain, we present efficient scheduling and timing analysis techniques to exploit the parallelization capabilities of many-core architectures and to derive tight and trustworthy Worst-Case Execution Time (WCET) estimates of CRTES.Los sistemas críticos empotrados de tiempo real (en ingles Critical Real-Time Embedded Systems, CRTES) se encargan de controlar partes fundamentales de los sistemas integrados, e.g. obtención de la energía de los paneles solares en satélites, la dirección y frenado en automóviles, o el control de vuelo en aviones. Para hacerlo, CRTES requieren fuerte evidencias del correcto comportamiento funcional y temporal. El primero garantiza que el sistema funciona correctamente en respuesta de sus entradas; el último asegura que sus operaciones se realizan dentro de unos limites temporales establecidos previamente. El objetivo de los CRTES es aumentar el número y la complejidad de las funciones. Algunos ejemplos incluyen los sistemas inteligentes de asistencia a la conducción en automóviles modernos o los sistemas avanzados de prevención de colisiones en vehiculos aereos no tripulados. Todas estas nuevas características, implementadas en software,conducen a un crecimiento exponencial tanto en los requerimientos de rendimiento como en la complejidad de desarrollo de software. Además, existe una gran necesidad de integrar múltiples funciones en una sóla plataforma para así reducir el número de unidades de procesamiento, cumplir con requisitos de peso y espacio, etc. En general, hay una clara necesidad de aumentar la potencia de cómputo de los actuales CRTES para soportar nueva funcionalidades sofisticadas y complejas e integrar múltiples sistemas en una sola plataforma. El uso de arquitecturas multi- y many-core se ve cada vez más en la industria CRTES como la solución para hacer frente a la demanda de mayor rendimiento y las limitaciones de costes de los futuros CRTES. Las arquitecturas many-core proporcionan un mayor rendimiento explotando el paralelismo de aplicaciones al tiempo que proporciona un mejor rendimiento por vatio ya que los cores se mantienen más simples con respecto a complejos procesadores de un solo core. Además, las capacidades de paralelización permiten programar múltiples funciones en el mismo procesador, maximizando la utilización del hardware. Sin embargo, el uso de multi- y many-core en CRTES también acarrea ciertos desafíos relacionados con la aportación de evidencias sobre el correcto funcionamiento del sistema, especialmente en el ámbito temporal. Por eso, a pesar de las ventajas de los procesadores many-core y del hecho de que éstos son una realidad en los sitemas integrados (por ejemplo Kalray MPPA, Freescale NXP P4080, TI Keystone II), su uso en CRTES aún precisa de la búsqueda de métodos eficientes para proveer evidencias fiables sobre el correcto funcionamiento del sistema. Esta tesis ahonda en el uso de procesadores many-core en CRTES como un medio para satisfacer los requisitos de rendimiento de aplicaciones complejas mientras proveen las garantías de tiempo necesarias. Para ello, esta tesis contribuye en el avance del estado del arte hacia la explotación de many-cores en CRTES en dos ámbitos de la computación. En el ámbito del hardware, esta tesis propone nuevos diseños many-core que posibilitan garantías de tiempo fiables y precisas. En el ámbito del software, la tesis presenta técnicas eficientes para la planificación de tareas y el análisis de tiempo para aprovechar las capacidades de paralelización en arquitecturas many-core, y también para derivar estimaciones de peor tiempo de ejecución (Worst-Case Execution Time, WCET) fiables y precisas

WCET Optimizations and Architectural Support for Hard Real-Time Systems

As time predictability is critical to hard real-time systems, it is not only necessary to accurately estimate the worst-case execution time (WCET) of the real-time tasks but also desirable to improve either the WCET of the tasks or time predictability of the system, because the real-time tasks with lower WCETs are easy to schedule and more likely to meat their deadlines. As a real-time system is an integration of software and hardware, the optimization can be achieved through two ways: software optimization and time-predictable architectural support. In terms of software optimization, we fi rst propose a loop-based instruction prefetching approach to further improve the WCET comparing with simple prefetching techniques such as Next-N-Line prefetching which can enhance both the average-case performance and the worst-case performance. Our prefetching approach can exploit the program controlow information to intelligently prefetch instructions that are most likely needed. Second, as inter-thread interferences in shared caches can signi cantly a ect the WCET of real-time tasks running on multicore processors, we study three multicore-aware code positioning methods to reduce the inter-core L2 cache interferences between co-running real-time threads. One strategy focuses on decreasing the longest WCET among the co-running threads, and two other methods aim at achieving fairness in terms of the amount or percentage of WCET reduction among co-running threads. In the aspect of time-predictable architectural support, we introduce the concept of architectural time predictability (ATP) to separate timing uncertainty concerns caused by hardware from software, which greatly facilitates the advancement of time-predictable processor design. We also propose a metric called Architectural Time-predictability Factor (ATF) to measure architectural time predictability quantitatively. Furthermore, while cache memories can generally improve average-case performance, they are harmful to time predictability and thus are not desirable for hard real-time and safety-critical systems. In contrast, Scratch-Pad Memories (SPMs) are time predictable, but they may lead to inferior performance. Guided by ATF, we propose and evaluate a variety of hybrid on-chip memory architectures to combine both caches and SPMs intelligently to achieve good time predictability and high performance. Detailed implementation and experimental results discussion are presented in this dissertation

Design for Time-Predictability

A large part of safety-critical embedded systems has to satisfy hard real-time constraints. These need sound methods and tools to derive reliable run-time guarantees. The guaranteed run times should not only be reliable, but also precise. The achievable precision highly depends on characteristics of the target architecture and the implementation methods and system layers of the software. Trends in hardware and software design run contrary to predictability. This article describes threats to time-predictability of systems and proposes design principles that support time predictability. The ultimate goal is to design performant systems with sharp upper and lower bounds on execution times

On the limits of probabilistic timing analysis

Over the last years, we are witnessing the steady and rapid growth of Critica! Real-Time Embedded Systems (CRTES) industries, such as automotive and aerospace. Many of the increasingly-complex CRTES' functionalities that are currently implemented with mechanical means are moving towards to an electromechanical implementation controlled by critica! software. This trend results in a two-fold consequence. First, the size and complexity of critical-software increases in every new embedded product. And second, high-performance hardware features like caches are more frequently used in real-time processors. The increase in complexity of CRTES challenges the validation and verification process, a necessary step to certify that the system is safe for deployment. Timing validation and verification includes the computation of the Worst-Case Execution Time (WCET) estimates, which need to be trustworthy and tight. Traditional timing analysis are challenged by the use of complex hardware/software, resulting in low-quality WCET estimates, which tend to add significant pessimism to guarantee estimates' trustworthiness. This calls for new solutions that help tightening WCET estimates in a safe manner. In this Thesis, we investigate the novel Measurement-Based Probabilistic Timing Analysis (MBPTA), which in its original version already shows potential to deliver trustworthy and tight WCETs for tasks running on complex systems. First, we propose a methodology to assess and ensure that ali cache memory layouts, which can significantly impact WCET, have been adequately factored in the WCET estimation process. Second, we provide a solution to achieve simultaneously cache representativeness and full path coverage. This solution provides evidence proving that WCET estimates obtained are valid for ali program execution paths regardless of how code and data are laid out in the cache. Lastly, we analyse and expose the main misconceptions and pitfalls that can prevent a sound application of WCET analysis based on extreme value theory, which is used as part of MBPTA.En los últimos años, se ha podido observar un crecimiento rápido y sostenido de la industria de los sistemas embebidos críticos de tiempo real (abreviado en inglés CRTES}, como por ejemplo la industria aeronáutica o la automovilística. En un futuro cercano, muchas de las funcionalidades complejas que actualmente se están implementando a través de sistemas mecánicos en los CRTES pasarán a ser controladas por software crítico. Esta tendencia tiene dos consecuencias claras. La primera, el tamaño y la complejidad del software se incrementará en cada nuevo producto embebido que se lance al mercado. La segunda, las técnicas hardware destinadas a alto rendimiento (por ejemplo, memorias caché) serán usadas más frecuentemente en los procesadores de tiempo real. El incremento en la complejidad de los CRTES impone un reto en los procesos de validación y verificación de los procesadores, un paso imprescindible para certificar que los sistemas se pueden comercializar de forma segura. La validación y verificación del tiempo de ejecución incluye la estimación del tiempo de ejecución en el peor caso (abreviado en inglés WCET}, que debe ser precisa y certera. Desafortunadamente, los procesos tradicionales para analizar el tiempo de ejecución tienen problemas para analizar las complejas combinaciones entre el software y el hardware, produciendo estimaciones del WCET de mala calidad y conservadoras. Para superar dicha limitación, es necesario que florezcan nuevas técnicas que ayuden a proporcionar WCET más precisos de forma segura y automatizada. En esta Tesis se profundiza en la investigación referente al análisis probabilístico de tiempo de ejecución basado en medidas (abreviado en inglés MBPTA), cuyas primeras implementaciones muestran potencial para obtener un WCET preciso y certero en tareas ejecutadas en sistemas complejos. Primero, se propone una metodología para certificar que todas las distribuciones de la memoria caché, una de las estructuras más complejas de los CRTES, han sido contabilizadas adecuadamente durante el proceso de estimación del WCET. Segundo, se expone una solución para conseguir a la vez representatividad en la memoria caché y cobertura total en caminos críticos del programa. Dicha solución garantiza que la estimación WCET obtenida es válida para todos los caminos de ejecución, independientemente de como el código y los datos se guardan en la memoria caché. Finalmente, se analizan y discuten los mayores malentendidos y obstáculos que pueden prevenir la aplicabilidad del análisis de WCET basado en la teoría de valores extremos, la cual forma parte del MBPTA.Postprint (published version

A Survey of Probabilistic Timing Analysis Techniques for Real-Time Systems

This survey covers probabilistic timing analysis techniques for real-time systems. It reviews and critiques the key results in the field from its origins in 2000 to the latest research published up to the end of August 2018. The survey provides a taxonomy of the different methods used, and a classification of existing research. A detailed review is provided covering the main subject areas: static probabilistic timing analysis, measurement-based probabilistic timing analysis, and hybrid methods. In addition, research on supporting mechanisms and techniques, case studies, and evaluations is also reviewed. The survey concludes by identifying open issues, key challenges and possible directions for future research