Energy-efficient thermal-aware multiprocessor scheduling for real-time tasks using TCPNs

We present an energy-effcient thermal-aware real-time global scheduler for a set of hard real-time (HRT) tasks running on a multiprocessor system. This global scheduler fulfills the thermal and temporal constraints by handling two independent variables, the task allocation time and the selection of clock frequency. To achieve its goal, the proposed scheduler is split into two stages. An off-line stage, based on a deadline partitioning scheme, computes the cycles that the HRT tasks must run per deadline interval at the minimum clock frequency to save energy while honoring the temporal and thermal constraints, and computes the maximum frequency at which the system can run below the maximum temperature. Then, an on-line, event-driven stage performs global task allocation applying a Fixed-Priority Zero-Laxity policy, reducing the overhead of quantum-based or interval-based global schedulers. The on-line stage embodies an adaptive scheduler that accepts or rejects soft RT aperiodic tasks throttling CPU frequency to the upper lowest available one to minimize power consumption while meeting time and thermal constraints. This approach leverages the best of two worlds: the off-line stage computes an ideal discrete HRT multiprocessor schedule, while the on-line stage manage soft real-time aperiodic tasks with minimum power consumption and maximum CPU utilization

Response Time Analysis for Thermal-Aware Real-Time Systems Under Fixed-Priority Scheduling

International audienceThis paper investigates schedulability analysis for thermal-aware real-time systems. Thermal constraints are becoming more and more critical in new generation miniaturized embedded systems, e.g. Medicals implants. As part of this work, we adapt the PFPasap algorithm proposed in [1] for energy-harvesting systems to thermal-aware ones. We prove its optimality for non-concrete1 fixed-priority task sets and propose a response-time analysis based on worst-case response-time upper bounds. We evaluate the efficacy of the proposed bounds via extensive simulation over randomly-generated task systems

Control techniques for thermal-aware energy-efficient real time multiprocessor scheduling

La utilización de microprocesadores multinúcleo no sólo es atractiva para la industria sino que en muchos ámbitos es la única opción. La planificación tiempo real sobre estas plataformas es mucho más compleja que sobre monoprocesadores y en general empeoran el problema de sobre-diseño, llevando a la utilización de muchos más procesadores /núcleos de los necesarios. Se han propuesto algoritmos basados en planificación fluida que optimizan la utilización de los procesadores, pero hasta el momento presentan en general inconvenientes que los alejan de su aplicación práctica, no siendo el menor el elevado número de cambios de contexto y migraciones.Esta tesis parte de la hipótesis de que es posible diseñar algoritmos basados en planificación fluida, que optimizan la utilización de los procesadores, cumpliendo restricciones temporales, térmicas y energéticas, con un bajo número de cambios de contexto y migraciones, y compatibles tanto con la generación fuera de línea de ejecutivos cíclicos atractivos para la industria, como de planificadores que integran técnicas de control en tiempo de ejecución que permiten la gestión eficiente tanto de tareas aperiódicas como de desviaciones paramétricas o pequeñas perturbaciones.A este respecto, esta tesis contribuye con varias soluciones. En primer lugar, mejora una metodología de modelo que representa todas las dimensiones del problema bajo un único formalismo (Redes de Petri Continuas Temporizadas). En segundo lugar, propone un método de generación de un ejecutivo cíclico, calculado en ciclos de procesador, para un conjunto de tareas tiempo real duro sobre multiprocesadores que optimiza la utilización de los núcleos de procesamiento respetando también restricciones térmicas y de energía, sobre la base de una planificación fluida. Considerar la sobrecarga derivada del número de cambios de contexto y migraciones en un ejecutivo cíclico plantea un dilema de causalidad: el número de cambios de contexto (y en consecuencia su sobrecarga) no se conoce hasta generar el ejecutivo cíclico, pero dicho número no se puede minimizar hasta que se ha calculado. La tesis propone una solución a este dilema mediante un método iterativo de convergencia demostrada que logra minimizar la sobrecarga mencionada.En definitiva, la tesis consigue explotar la idea de planificación fluida para maximizar la utilización (donde maximizar la utilización es un gran problema en la industria) generando un sencillo ejecutivo cíclico de mínima sobrecarga (ya que la sobrecarga implica un gran problema de los planificadores basados en planificación fluida).Finalmente, se propone un método para utilizar las referencias de la planificación fuera de línea establecida en el ejecutivo cíclico para su seguimiento por parte de un controlador de frecuencia en línea, de modo que se pueden afrontar pequeñas perturbaciones y variaciones paramétricas, integrando la gestión de tareas aperiódicas (tiempo real blando) mientras se asegura la integridad de la ejecución del conjunto de tiempo real duro.Estas aportaciones constituyen una novedad en el campo, refrendada por las publicaciones derivadas de este trabajo de tesis.<br /

Thermal-aware resource allocation in earliest deadline first using fluid scheduling

Thermal issues in microprocessors have become a major design constraint because of their adverse effects on the reliability, performance and cost of the system. This article proposes an improvement in earliest deadline first, a uni-processor scheduling algorithm, without compromising its optimality in order to reduce the thermal peaks and variations. This is done by introducing a factor of fairness to earliest deadline first algorithm, which introduces idle intervals during execution and allows uniform distribution of workload over the time. The technique notably lowers the number of context switches when compare with the previous thermal-aware scheduling algorithm based on the same amount of fairness. Although, the algorithm is proposed for uni-processor environment, it is also applicable to partitioned scheduling in multi-processor environment, which primarily converts the multi-processor scheduling problem to a set of uni-processor scheduling problem and thereafter uses a uni-processor scheduling technique for scheduling. The simulation results show that the proposed approach reduces up to 5% of the temperature peaks and variations in a uni-processor environment while reduces up to 7% and 6% of the temperature spatial gradient and the average temperature in multi-processor environment, respectively

A Control-Theoretic Design And Analysis Framework For Resilient Hard Real-Time Systems

We introduce a new design metric called system-resiliency which characterizes the maximum unpredictable external stresses that any hard-real-time performance mode can withstand. Our proposed systemresiliency framework addresses resiliency determination for real-time systems with physical and hardware limitations. Furthermore, our framework advises the system designer about the feasible trade-offs between external system resources for the system operating modes on a real-time system that operates in a multi-parametric resiliency environment. Modern multi-modal real-time systems degrade the system’s operational modes as a response to unpredictable external stimuli. During these mode transitions, real-time systems should demonstrate a reliable and graceful degradation of service. Many control-theoretic-based system design approaches exist. Although they permit real-time systems to operate under various physical constraints, none of them allows the system designer to predict the system-resiliency over multi-constrained operating environment. Our framework fills this gap; the proposed framework consists of two components: the design-phase and runtime control. With the design-phase analysis, the designer predicts the behavior of the real-time system for variable external conditions. Also, the runtime controller navigates the system to the best desired target using advanced control-theoretic techniques. Further, our framework addresses the system resiliency of both uniprocessor and multicore processor systems. As a proof of concept, we first introduce a design metric called thermal-resiliency, which characterizes the maximum external thermal stress that any hard-real-time performance mode can withstand. We verify the thermal-resiliency for the external thermal stresses on a uniprocessor system through a physical testbed. We show how to solve some of the issues and challenges of designing predictable real-time systems that guarantee hard deadlines even under transitions between modes in an unpredictable thermal environment where environmental temperature may dynamically change using our new metric. We extend the derivation of thermal-resiliency to multicore systems and determine the limitations of external thermal stress that any hard-real-time performance mode can withstand. Our control-theoretic framework allows the system designer to allocate asymmetric processing resources upon a multicore proiii cessor and still maintain thermal constraints. In addition, we develop real-time-scheduling sub-components that are necessary to fully implement our framework; toward this goal, we investigate the potential utility of parallelization for meeting real-time constraints and minimizing energy. Under malleable gang scheduling of implicit-deadline sporadic tasks upon multiprocessors, we show the non-necessity of dynamic voltage/frequency regarding optimality of our scheduling problem. We adapt the canonical schedule for DVFS multiprocessor platforms and propose a polynomial-time optimal processor/frequency-selection algorithm. Finally, we verify the correctness of our framework through multiple measurable physical and hardware constraints and complete our work on developing a generalized framework

Advanced engineering - Communications systems research

Communications systems research on information systems and on digital telemetry and command in Deep Space Networ

On the Design of Real-Time Systems on Multi-Core Platforms under Uncertainty

Real-time systems are computing systems that demand the assurance of not only the logical correctness of computational results but also the timing of these results. To ensure timing constraints, traditional real-time system designs usually adopt a worst-case based deterministic approach. However, such an approach is becoming out of sync with the continuous evolution of IC technology and increased complexity of real-time applications. As IC technology continues to evolve into the deep sub-micron domain, process variation causes processor performance to vary from die to die, chip to chip, and even core to core. The extensive resource sharing on multi-core platforms also significantly increases the uncertainty when executing real-time tasks. The traditional approach can only lead to extremely pessimistic, and thus, unpractical design of real-time systems. Our research seeks to address the uncertainty problem when designing real-time systems on multi-core platforms. We first attacked the uncertainty problem caused by process variation. We proposed a virtualization framework and developed techniques to optimize the system\u27s performance under process variation. We further studied the problem on peak temperature minimization for real-time applications on multi-core platforms. Three heuristics were developed to reduce the peak temperature for real-time systems. Next, we sought to address the uncertainty problem in real-time task execution times by developing statistical real-time scheduling techniques. We studied the problem of fixed-priority real-time scheduling of implicit periodic tasks with probabilistic execution times on multi-core platforms. We further extended our research for tasks with explicit deadlines. We introduced the concept of harmonic to a more general task set, i.e. tasks with explicit deadlines, and developed new task partitioning techniques. Throughout our research, we have conducted extensive simulations to study the effectiveness and efficiency of our developed techniques. The increasing process variation and the ever-increasing scale and complexity of real-time systems both demand a paradigm shift in the design of real-time applications. Effectively dealing with the uncertainty in design of real-time applications is a challenging but also critical problem. Our research is such an effort in this endeavor, and we conclude this dissertation with discussions of potential future work

Adaptive CPU Resource Management for Multicore Platforms

The topic of this thesis is adaptive CPU resource management for multicore platforms. The work was done as a part of the resource manager component of the adaptive resource management framework implemented in the European ACTORS project. The framework dynamically allocates CPU resources for the applications. The key element of the framework is the resource manager that combines feedforward and feedback algorithms together with reservation techniques. The reservation techniques are supported by a new Linux scheduler through hard constant bandwidth server reservations. The resource requirements of the applications are provided through service level tables. Dynamic bandwidth allocation is performed by the resource manager which adapts applications to changes in resource availability, and adapts the resource allocation to changes in application requirements. The dynamic bandwidth allocation allows to obtain real application models through the tuning and update of the initial service level table