Scratchpad Memory Management For Multicore Real-Time Embedded Systems

Multicore systems will continue to spread in the domain of real-time embedded systems due to the increasing need for high-performance applications. This research discusses some of the challenges associated with employing multicore systems for safety-critical real-time applications. Mainly, this work is concerned with providing: 1) efficient inter-core timing isolation for independent tasks, and 2) predictable task communication for communicating tasks. Principally, we introduce a new task execution model, based on the 3-phase execution model, that exploits the Direct Memory Access (DMA) controllers available in modern embedded platforms along with ScratchPad Memories (SPMs) to enforce strong timing isolation between tasks. The DMA and the SPMs are explicitly managed to pre-load tasks from main memory into the local (private) scratchpad memories. Tasks are then executed from the local SPMs without accessing main memory. This model allows CPU execution to be overlapped with DMA loading/unloading operations from and to main memory. We show that by co-scheduling task execution on CPUs and using DMA to access memory and I/O, we can efficiently hide access latency to physical resources. In turn, this leads to significant improvements in system schedulability, compared to both the case of unregulated contention for access to physical resources and to previous cache and SPM management techniques for real-time systems. The presented SPM-centric scheduling algorithms and analyses cover single-core, partitioned, and global real-time systems. The proposed scheme is also extended to support large tasks that do not fit entirely into the local SPM. Moreover, the schedulability analysis considers the case of recovering from transient soft errors (bit flips caused by a single event upset) in several levels of memories, that cannot be automatically corrected in hardware by the ECC unit. The proposed SPM-centric scheduling is integrated at the OS level; thus it is transparent to applications. The proposed scheme is implemented and evaluated on an FPGA platform and a Commercial-Off-The-Shelf (COTS) platform. In regards to real-time task communication, two types of communication are considered. 1) Asynchronous inter-task communication, between either sequential tasks (single-threaded) or parallel tasks (multi-threaded). 2) Intra-task communication, where parallel threads of the same application exchange data. A new task scheduling model for parallel tasks (Bundled Scheduling) is proposed to facilitate intra-task communication and reduce synchronization overheads. We show that the proposed bundled scheduling model can be applied to several parallel programming models, such as fork-join and DAG-based applications, leading to improved system schedulability. Finally, intra-task communication is governed by a predictable inter-core communication platform. Specifically, we propose HopliteRT, a lean and predictable Network-on-Chip that connects the private SPMs

Flit Scheduling for Cut-through Switching: Towards Near-Zero End-to-end Latency

Achieving low end-to-end latency with high reliability is one of the key objectives for future mission-critical applications, like the Tactile Internet and real-time interactive Virtual/Augmented Reality (VR/AR). To serve the purpose, cut-through (CT) switching is a promising approach to significantly reduce the transmission delay of store-and-forward switching, via flit-ization of a packet and concurrent forwarding of the flits belonging to the same packet. CT switching, however, has been applied only to well-controlled scenarios like network-on-chip and data center networks, and hence flit scheduling in heterogeneous environments (e.g., the Internet and wide area network) has been given little attention. This paper tries to fill the gap to facilitate the adoption of CT switching in the general-purpose data networks. In particular, we first introduce a packet discarding technique that sheds the packet expected to violate its delay requirement and then propose two flit scheduling algorithms, fEDF (flit-based Earliest Deadline First) and fSPF (flit-based Shortest Processing-time First), aiming at enhancing both reliability and end-to-end latency. Considering packet delivery ratio (PDR) as a reliability metric, we performed extensive simulations to show that the proposed scheduling algorithms can enhance PDR by up to 30.11% (when the delay requirement is 7 ms) and the average end-to-end latency by up to 13.86% (when the delay requirement is 10 ms), against first-in first-out (FIFO) scheduling

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

NoC-based Architectures for Real-Time Applications : Performance Analysis and Design Space Exploration

Monoprocessor architectures have reached their limits in regard to the computing power they offer vs the needs of modern systems. Although multicore architectures partially mitigate this limitation and are commonly used nowadays, they usually rely on intrinsically non-scalable buses to interconnect the cores. The manycore paradigm was proposed to tackle the scalability issue of bus-based multicore processors. It can scale up to hundreds of processing elements (PEs) on a single chip, by organizing them into computing tiles (holding one or several PEs). Intercore communication is usually done using a Network-on-Chip (NoC) that consists of interconnected onchip routers allowing communication between tiles. However, manycore architectures raise numerous challenges, particularly for real-time applications. First, NoC-based communication tends to generate complex blocking patterns when congestion occurs, which complicates the analysis, since computing accurate worst-case delays becomes difficult. Second, running many applications on large Systems-on-Chip such as manycore architectures makes system design particularly crucial and complex. On one hand, it complicates Design Space Exploration, as it multiplies the implementation alternatives that will guarantee the desired functionalities. On the other hand, once a hardware architecture is chosen, mapping the tasks of all applications on the platform is a hard problem, and finding an optimal solution in a reasonable amount of time is not always possible. Therefore, our first contributions address the need for computing tight worst-case delay bounds in wormhole NoCs. We first propose a buffer-aware worst-case timing analysis (BATA) to derive upper bounds on the worst-case end-to-end delays of constant-bit rate data flows transmitted over a NoC on a manycore architecture. We then extend BATA to cover a wider range of traffic types, including bursty traffic flows, and heterogeneous architectures. The introduced method is called G-BATA for Graph-based BATA. In addition to covering a wider range of assumptions, G-BATA improves the computation time; thus increases the scalability of the method. In a second part, we develop a method addressing design and mapping for applications with real-time constraints on manycore platforms. It combines model-based engineering tools (TTool) and simulation with our analytical verification technique (G-BATA) and tools (WoPANets) to provide an efficient design space exploration framework. Finally, we validate our contributions on (a) a serie of experiments on a physical platform and (b) two case studies taken from the real world: an autonomous vehicle control application, and a 5G signal decoder applicatio

Compilation de systèmes temps réel

I introduce and advocate for the concept of Real-Time Systems Compilation. By analogy with classical compilation, real-time systems compilation consists in the fully automatic construction of running, correct-by-construction implementations from functional and non-functional specifications of embedded control systems. Like in a classical compiler, the whole process must be fast (thus enabling a trial-and-error design style) and produce reasonably efficient code. This requires the use of fast heuristics, and the use of fine-grain platform and application models. Unlike a classical compiler, a real-time systems compiler must take into account non-functional properties of a system and ensure the respect of non-functional requirements (in addition to functional correctness). I also present Lopht, a real-time systems compiler for statically-scheduled real-time systems we built by combining techniques and concepts from real-time scheduling, compilation, and synchronous languages

High-Performance and Time-Predictable Embedded Computing

Nowadays, the prevalence of computing systems in our lives is so ubiquitous that we live in a cyber-physical world dominated by computer systems, from pacemakers to cars and airplanes. These systems demand for more computational performance to process large amounts of data from multiple data sources with guaranteed processing times. Actuating outside of the required timing bounds may cause the failure of the system, being vital for systems like planes, cars, business monitoring, e-trading, etc. High-Performance and Time-Predictable Embedded Computing presents recent advances in software architecture and tools to support such complex systems, enabling the design of embedded computing devices which are able to deliver high-performance whilst guaranteeing the application required timing bounds. Technical topics discussed in the book include: Parallel embedded platforms Programming models Mapping and scheduling of parallel computations Timing and schedulability analysis Runtimes and operating systems The work reflected in this book was done in the scope of the European project P SOCRATES, funded under the FP7 framework program of the European Commission. High-performance and time-predictable embedded computing is ideal for personnel in computer/communication/embedded industries as well as academic staff and master/research students in computer science, embedded systems, cyber-physical systems and internet-of-things.info:eu-repo/semantics/publishedVersio

High Performance Embedded Computing

Nowadays, the prevalence of computing systems in our lives is so ubiquitous that we live in a cyber-physical world dominated by computer systems, from pacemakers to cars and airplanes. These systems demand for more computational performance to process large amounts of data from multiple data sources with guaranteed processing times. Actuating outside of the required timing bounds may cause the failure of the system, being vital for systems like planes, cars, business monitoring, e-trading, etc. High-Performance and Time-Predictable Embedded Computing presents recent advances in software architecture and tools to support such complex systems, enabling the design of embedded computing devices which are able to deliver high-performance whilst guaranteeing the application required timing bounds. Technical topics discussed in the book include: Parallel embedded platforms Programming models Mapping and scheduling of parallel computations Timing and schedulability analysis Runtimes and operating systemsThe work reflected in this book was done in the scope of the European project P SOCRATES, funded under the FP7 framework program of the European Commission. High-performance and time-predictable embedded computing is ideal for personnel in computer/communication/embedded industries as well as academic staff and master/research students in computer science, embedded systems, cyber-physical systems and internet-of-things

Vorhersagbares und zur Laufzeit adaptierbares On-Chip Netzwerk für gemischt kritische Echtzeitsysteme

The industry of safety-critical and dependable embedded systems calls for even cheaper, high performance platforms that allow flexibility and an efficient verification of safety and real-time requirements. To cope with the increasing complexity of interconnected functions and to reduce the cost and power consumption of the system, multicore systems are used to efficiently integrate different processing units in the same chip. Networks-on-chip (NoCs), as a modular interconnect, are used as a promising solution for such multiprocessor systems on chip (MPSoCs), due to their scalability and performance. For safety-critical systems, a major goal is the avoidance of hazards. For this, safety-critical systems are qualified or even certified to prove the correctness of the functioning under all possible cases. A predictable behaviour of the NoC can help to ease the qualification process of the system. To achieve the required predictability, designers have two classes of solutions: quality of service mechanisms and (formal) analysis. For mixed-criticality systems, isolation and analysis approaches must be combined to efficiently achieve the desired predictability. Traditional NoC analysis and architecture concepts tackle only a subpart of the challenges: they focus on either performance or predictability. Existing, predictable NoCs are deemed too expensive and inflexible to host a variety of applications with opposing constraints. And state-of-the-art analyses neglect certain platform properties to verify the behaviour. Together this leads to a high over-provisioning of the hardware resources as well as adverse impacts on system performance, and on the flexibility of the system. In this work we tackle these challenges and develop a predictable and runtime-adaptable NoC architecture that efficiently integrates mixed-critical applications with opposing constraints. Additionally, we present a modelling and analysis framework for NoCs that accounts for backpressure. This framework enables to evaluate the performance and reliability early at design time. Hence, the designer can assess multiple design decisions by using abstract models and formal approaches.Die Industrie der sicherheitskritischen und zuverlässigen eingebetteten Systeme verlangt nach noch günstigeren, leistungsfähigeren Plattformen, welche Flexibilität und eine effiziente Überprüfung der Sicherheits- und Echtzeitanforderungen ermöglichen. Um der zunehmenden Komplexität der zunehmend vernetzten Funktionen gerecht zu werden und die Kosten und den Stromverbrauch eines Systems zu reduzieren, werden Mehrkern-Systeme eingesetzt. On-Chip Netzwerke werden aufgrund ihrer Skalierbarkeit und Leistung als vielversprechende Lösung für solch Mehrkern-Systeme eingesetzt. Bei sicherheitskritischen Systemen ist die Vermeidung von Gefahren ein wesentliches Ziel. Dazu werden sicherheitskritische Systeme qualifiziert oder zertifiziert, um die Funktionsfähigkeit in allen möglichen Fällen nachzuweisen. Ein vorhersehbares Verhalten des on-Chip Netzwerks kann dabei helfen, den Qualifizierungsprozess des Systems zu erleichtern. Um die erforderliche Vorhersagbarkeit zu erreichen, gibt es zwei Klassen von Lösungen: Quality of Service Mechanismen und (formale) Analyse. Für Systeme mit gemischter Relevanz müssen Isolationsmechanismen und Analyseansätze kombiniert werden, um die gewünschte Vorhersagbarkeit effizient zu erreichen. Traditionelle Analyse- und Architekturkonzepte für on-Chip Netzwerke lösen nur einen Teil dieser Herausforderungen: sie konzentrieren sich entweder auf Leistung oder Vorhersagbarkeit. Existierende vorhersagbare on-Chip Netzwerke werden als zu teuer und unflexibel erachtet, um eine Vielzahl von Anwendungen mit gegensätzlichen Anforderungen zu integrieren. Und state-of-the-art Analysen vernachlässigen bzw. vereinfachen bestimmte Plattformeigenschaften, um das Verhalten überprüfen zu können. Dies führt zu einer hohen Überbereitstellung der Hardware-Ressourcen als auch zu negativen Auswirkungen auf die Systemleistung und auf die Flexibilität des Systems. In dieser Arbeit gehen wir auf diese Herausforderungen ein und entwickeln eine vorhersehbare und zur Laufzeit anpassbare Architektur für on-Chip Netzwerke, welche gemischt-kritische Anwendungen effizient integriert. Zusätzlich stellen wir ein Modellierungs- und Analyseframework für on-Chip Netzwerke vor, das den Paketrückstau berücksichtigt. Dieses Framework ermöglicht es, Designentscheidungen anhand abstrakter Modelle und formaler Ansätze frühzeitig beurteilen