WCET Analysis of a Parallel 3D Multigrid Solver Executed on the MERASA Multi-Core

To meet performance requirements as well as constraints on cost and power consumption, future embedded systems will be designed with multi-core processors. However, the question of timing analysability is raised with these architectures. In the MERASA project, a WCET-aware multi-core processor has been designed with the appropriate system software. They both guarantee that the WCET of tasks running on different cores can be safely analyzed since their possible interactions can be bounded. Nevertheless, computing the WCET of a parallel application is still not straightforward and a high-level preliminary analysis of the communication and synchronization patterns must be performed. In this paper, we report on our experience in evaluating the WCET of a parallel 3D multigrid solver code and we propose lines for further research on this topic

A static scheduling approach to enable safety-critical OpenMP applications

Parallel computation is fundamental to satisfy the performance requirements of advanced safety-critical systems. OpenMP is a good candidate to exploit the performance opportunities of parallel platforms. However, safety-critical systems are often based on static allocation strategies, whereas current OpenMP implementations are based on dynamic schedulers. This paper proposes two OpenMP-compliant static allocation approaches: an optimal but costly approach based on an ILP formulation, and a sub-optimal but tractable approach that computes a worst-case makespan bound close to the optimal one.This work is funded by the EU projects P-SOCRATES (FP7-ICT-2013-10) and HERCULES (H2020/ICT/2015/688860), and the Spanish Ministry of Science and Innovation under contract TIN2015-65316-P.Peer ReviewedPostprint (author's final draft

OTAWA: An Open Toolbox for Adaptive WCET Analysis

International audienceThe analysis of worst-case execution times has become mandatory in the design of hard real-time systems: it is absolutely necessary to know an upper bound of the execution time of each task to determine a task schedule that insures that deadlines will all be met. The OTAWA toolbox presented in this paper has been designed to host algorithms resulting from research in the domain of WCET analysis so that they can be combined to compute tight WCET estimates. It features an abstraction layer that decouples the analyses from the target hardware and from the instruction set architecture, as well as a set of functionalities that facilitate the implementation of new approaches

Automatic WCET Analysis of Real-Time Parallel Applications

National audienceTomorrow’s real-time embedded systems will be built upon multicore architectures. This raises two challenges. First, shared resources should be arbitrated in such a way that the WCET of independent threads running concurrently can be computed: in this paper, we assume that time-predictable multicore architectures are available. The second challenge is to develop software that achieves a high level of performance without impairing timing predictability. We investigate parallel software based on the POSIX threads standard and we show how the WCET of a parallel program can be analysed. We report experimental results obtained for typical parallel programs with an extended version of the OTAWA toolset

Toward Static Timing Analysis of Parallel Software

The current trend within computer, and even real-time, systems is to incorporate parallel hardware, e.g., multicore processors, and parallel software. Thus, the ability to safely analyse such parallel systems, e.g., regarding the timing behaviour, becomes necessary. Static timing analysis is an approach to mathematically derive safe bounds on the execution time of a program, when executed on a given hardware platform. This paper presents an algorithm that statically analyses the timing of parallel software, with threads communicating through shared memory, using abstract interpretation. It also gives an extensive example to clarify how the algorithm works

A Multi-core processor for hard real-time systems

The increasing demand for new functionalities in current and future hard real-time embedded systems, like the ones deployed in automotive and avionics industries, is driving an increment in the performance required in current embedded processors. Multi-core processors represent a good design solution to cope with such higher performance requirements due to their better performance-per-watt ratio while maintaining the core design simple. Moreover, multi-cores also allow executing mixed-criticality level workloads composed of tasks with and without hard real-time requirements, maximizing the utilization of the hardware resources while guaranteeing low cost and low power consumption. Despite those benefits, current multi-core processors are less analyzable than single-core ones due to the interferences between different tasks when accessing hardware shared resources. As a result, estimating a meaningful Worst-Case Execution Time (WCET) estimation - i.e. to compute an upper bound of the application's execution time - becomes extremely difficult, if not even impossible, because the execution time of a task may change depending on the other threads running at the same time. This makes the WCET of a task dependent on the set of inter-task interferences introduced by the co-running tasks. Providing a WCET estimation independent from the other tasks (time composability property) is a key requirement in hard real-time systems. This thesis proposes a new multi-core processor design in which time composability is achieved, hence enabling the use of multi-cores in hard real-time systems. With our proposals the WCET estimation of a HRT is independent from the other co-running tasks. To that end, we design a multi-core processor in which the maximum delay a request from a Hard Real-time Task (HRT), accessing a hardware shared resource can suffer due to other tasks is bounded: our processor guarantees that a request to a shared resource cannot be delayed longer than a given Upper Bound Delay (UBD). In addition, the UBD allows identifying the impact that different processor configurations may have on the WCET by determining the sensitivity of a HRT to different resource allocations. This thesis proposes an off-line task allocation algorithm (called IA3: Interference-Aware Allocation Algorithm), that allocates tasks in a task set based on the HRT's sensitivity to different resource allocations. As a result the hardware shared resources used by HRTs are minimized, by allowing Non Hard Real-time Tasks (NHRTs) to use the rest of resources. Overall, our proposals provide analyzability for the HRTs allowing NHRTs to be executed into the same chip without any effect on the HRTs. The previous first two proposals of this thesis focused on supporting the execution of multi-programmed workloads with mixed-criticality levels (composed of HRTs and NHRTs). Higher performance could be achieved by implementing multi-threaded applications. As a first step towards supporting hard real-time parallel applications, this thesis proposes a new hardware/software approach to guarantee a predictable execution of software pipelined parallel programs. This thesis also investigates a solution to verify the timing correctness of HRTs without requiring any modification in the core design: we design a hardware unit which is interfaced with the processor and integrated into a functional-safety aware methodology. This unit monitors the execution time of a block of instructions and it detects if it exceeds the WCET. Concretely, we show how to handle timing faults on a real industrial automotive platform.La creciente demanda de nuevas funcionalidades en los sistemas empotrados de tiempo real actuales y futuros en industrias como la automovilística y la de aviación, está impulsando un incremento en el rendimiento necesario en los actuales procesadores empotrados. Los procesadores multi-núcleo son una solución eficiente para obtener un mayor rendimiento ya que aumentan el rendimiento por vatio, manteniendo el diseño del núcleo simple. Por otra parte, los procesadores multi-núcleo también permiten ejecutar cargas de trabajo con niveles de tiempo real mixtas (formadas por tareas de tiempo real duro y laxo así como tareas sin requerimientos de tiempo real), maximizando así la utilización de los recursos de procesador y garantizando el bajo consumo de energía. Sin embargo, a pesar los beneficios mencionados anteriormente, los actuales procesadores multi-núcleo son menos analizables que los de un solo núcleo debido a las interferencias surgidas cuando múltiples tareas acceden simultáneamente a los recursos compartidos del procesador. Como resultado, la estimación del peor tiempo de ejecución (conocido como WCET) - es decir, una cota superior del tiempo de ejecución de la aplicación - se convierte en extremadamente difícil, si no imposible, porque el tiempo de ejecución de una tarea puede cambiar dependiendo de las otras tareas que se estén ejecutando concurrentemente. Determinar una estimación del WCET independiente de las otras tareas es un requisito clave en los sistemas empotrados de tiempo real duro. Esta tesis propone un nuevo diseño de procesador multi-núcleo en el que el tiempo de ejecución de las tareas se puede componer, lo que permitirá el uso de procesadores multi-núcleo en los sistemas de tiempo real duro. Para ello, diseñamos un procesador multi-núcleo en el que la máxima demora que puede sufrir una petición de una tarea de tiempo real duro (HRT) para acceder a un recurso hardware compartido debido a otras tareas está acotado, tiene un límite superior (UBD). Además, UBD permite identificar el impacto que las diferentes posibles configuraciones del procesador pueden tener en el WCET, mediante la determinación de la sensibilidad en la variación del tiempo de ejecución de diferentes reservas de recursos del procesador. Esta tesis propone un algoritmo estático de reserva de recursos (llamado IA3), que asigna tareas a núcleos en función de dicha sensibilidad. Como resultado los recursos compartidos del procesador usados por tareas HRT se reducen al mínimo, permitiendo que las tareas sin requerimiento de tiempo real (NHRTs) puedas beneficiarse del resto de recursos. Por lo tanto, las propuestas presentadas en esta tesis permiten el análisis del WCET para tareas HRT, permitiendo así mismo la ejecución de tareas NHRTs en el mismo procesador multi-núcleo, sin que estas tengan ningún efecto sobre las tareas HRT. Las propuestas presentadas anteriormente se centran en el soporte a la ejecución de múltiples cargas de trabajo con diferentes niveles de tiempo real (HRT y NHRTs). Sin embargo, un mayor rendimiento puede lograrse mediante la transformación una tarea en múltiples sub-tareas paralelas. Esta tesis propone una nueva técnica, con soporte del procesador y del sistema operativo, que garantiza una ejecución analizable del modelo de ejecución paralela software pipelining. Esta tesis también investiga una solución para verificar la corrección del WCET de HRT sin necesidad de ninguna modificación en el diseño de la base: un nuevo componente externo al procesador se conecta a este sin necesidad de modificarlo. Esta nueva unidad monitorea el tiempo de ejecución de un bloque de instrucciones y detecta si se excede el WCET. Esta unidad permite detectar fallos de sincronización en sistemas de computación utilizados en automóviles

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

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

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

Scheduling techniques to improve the worst-case execution time of real-time parallel applications on heterogeneous platforms

The key to providing high performance and energy-efficient execution for hard real-time applications is the time predictable and efficient usage of heterogeneous multiprocessors. However, schedulability analysis of parallel applications executed on unrelated heterogeneous multiprocessors is challenging and has not been investigated adequately by earlier works. The unrelated model is suitable to represent many of the multiprocessor platforms available today because a task (i.e., sequential code) may exhibit a different work-case-execution-time (WCET) on each type of processor on an unrelated heterogeneous multiprocessors platform. A parallel application can be realistically modeled as a directed acyclic graph (DAG), where the nodes are sequential tasks and the edges are dependencies among the tasks. This thesis considers a sporadic DAG model which is used broadly to analyze and verify the real-time requirements of parallel applications. A global work-conserving scheduler can efficiently utilize an unrelated platform by executing the tasks of a DAG on different processor types. However, it is challenging to compute an upper bound on the worst-case schedule length of the DAG, called makespan, which is used to verify whether the deadline of a DAG is met or not. There are two main challenges. First, because of the heterogeneity of the processors, the WCET for each task of the DAG depends on which processor the task is executing on during actual runtime. Second, timing anomalies are the main obstacle to compute the makespan even for the simpler case when all the processors are of the same type, i.e., homogeneous multiprocessors. To that end, this thesis addresses the following problem: How we can schedule multiple sporadic DAGs on unrelated multiprocessors such that all the DAGs meet their deadlines. Initially, the thesis focuses on homogeneous multiprocessors that is a special case of unrelated multiprocessors to understand and tackle the main challenge of timing anomalies. A novel timing-anomaly-free scheduler is proposed which can be used to compute the makespan of a DAG just by simulating the execution of the tasks based on this proposed scheduler. A set of representative task-based parallel OpenMP applications from the BOTS benchmark suite are modeled as DAGs to investigate the timing behavior of real-world applications. A simulation framework is developed to evaluate the proposed method. Furthermore, the thesis targets unrelated multiprocessors and proposes a global scheduler to execute the tasks of a single DAG to an unrelated multiprocessors platform. Based on the proposed scheduler, methods to compute the makespan of a single DAG are introduced. A set of representative parallel applications from the BOTS benchmark suite are modeled as DAGs that execute on unrelated multiprocessors. Furthermore, synthetic DAGs are generated to examine additional structures of parallel applications and various platform capabilities. A simulation framework that simulates the execution of the tasks of a DAG on an unrelated multiprocessor platform is introduced to assess the effectiveness of the proposed makespan computations. Finally, based on the makespan computation of a single DAG this thesis presents the design and schedulability analysis of global and federated scheduling of sporadic DAGs that execute on unrelated multiprocessors