523 research outputs found

    Dynamic voltage scaling under EDF revisited

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    The original publication is available at www.springerlink.comInternational audienceBasic algorithms have been proposed in the field of low-power (Yao, F., et al. in Proceedings of lEEE annual foundations of computer science, pp. 374–382, 1995) which compute the minimum energy-schedule for a set of non-recurrent tasks (or jobs) scheduled under EDF on a dynamically variable voltage processor. In this study, we propose improvements upon existing algorithms with lower average and worst-case complexities. They are based on a new EDF feasibility test that helps to identify the “critical intervals”. The complexity of this feasibility test depends on structural characteristics of the set of jobs. More precisely, it depends on how tasks are included one in the other. The first step of the algorithm is to construct the Hasse diagram of the set of tasks where the partial order is defined by the inclusion relation on the tasks. Then, the algorithm constructs the shortest path in a geometrical representation at each level of the Hasse diagram. The optimal processor speed is chosen according to the maximal slope of each path

    A survey of offline algorithms for energy minimization under deadline constraints

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    Modern computers allow software to adjust power management settings like speed and sleep modes to decrease the power consumption, possibly at the price of a decreased performance. The impact of these techniques mainly depends on the schedule of the tasks. In this article, a survey on underlying theoretical results on power management, as well as offline scheduling algorithms that aim at minimizing the energy consumption under real-time constraints, is given

    Resource-aware scheduling for 2D/3D multi-/many-core processor-memory systems

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    This dissertation addresses the complexities of 2D/3D multi-/many-core processor-memory systems, focusing on two key areas: enhancing timing predictability in real-time multi-core processors and optimizing performance within thermal constraints. The integration of an increasing number of transistors into compact chip designs, while boosting computational capacity, presents challenges in resource contention and thermal management. The first part of the thesis improves timing predictability. We enhance shared cache interference analysis for set-associative caches, advancing the calculation of Worst-Case Execution Time (WCET). This development enables accurate assessment of cache interference and the effectiveness of partitioned schedulers in real-world scenarios. We introduce TCPS, a novel task and cache-aware partitioned scheduler that optimizes cache partitioning based on task-specific WCET sensitivity, leading to improved schedulability and predictability. Our research explores various cache and scheduling configurations, providing insights into their performance trade-offs. The second part focuses on thermal management in 2D/3D many-core systems. Recognizing the limitations of Dynamic Voltage and Frequency Scaling (DVFS) in S-NUCA many-core processors, we propose synchronous thread migrations as a thermal management strategy. This approach culminates in the HotPotato scheduler, which balances performance and thermal safety. We also introduce 3D-TTP, a transient temperature-aware power budgeting strategy for 3D-stacked systems, reducing the need for Dynamic Thermal Management (DTM) activation. Finally, we present 3QUTM, a novel method for 3D-stacked systems that combines core DVFS and memory bank Low Power Modes with a learning algorithm, optimizing response times within thermal limits. This research contributes significantly to enhancing performance and thermal management in advanced processor-memory systems

    Dynamics analysis and integrated design of real-time control systems

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    Real-time control systems are widely deployed in many applications. Theory and practice for the design and deployment of real-time control systems have evolved significantly. From the design perspective, control strategy development has been the focus of the research in the control community. In order to develop good control strategies, process modelling and analysis have been investigated for decades, and stability analysis and model-based control have been heavily studied in the literature. From the implementation perspective, real-time control systems require timeliness and predictable timing behaviour in addition to logical correctness, and a real-time control system may behave very differently with different software implementations of the control strategies on a digital controller, which typically has limited computing resources. Most current research activities on software implementations concentrate on various scheduling methodologies to ensure the schedulability of multiple control tasks in constrained environments. Recently, more and more real-time control systems are implemented over data networks, leading to increasing interest worldwide in the design and implementation of networked control systems (NCS). Major research activities in NCS include control-oriented and scheduling-oriented investigations. In spite of significant progress in the research and development of real-time control systems, major difficulties exist in the state of the art. A key issue is the lack of integrated design for control development and its software implementation. For control design, the model-based control technique, the current focus of control research, does not work when a good process model is not available or is too complicated for control design. For control implementation on digital controllers running multiple tasks, the system schedulability is essential but is not enough; the ultimate objective of satisfactory quality-of-control (QoC) performance has not been addressed directly. For networked control, the majority of the control-oriented investigations are based on two unrealistic assumptions about the network induced delay. The scheduling-oriented research focuses on schedulability and does not directly link to the overall QoC of the system. General solutions with direct QoC consideration from the network perspective to the challenging problems of network delay and packet dropout in NCS have not been found in the literature. This thesis addresses the design and implementation of real-time control systems with regard to dynamics analysis and integrated design. Three related areas have been investigated, namely control development for controllers, control implementation and scheduling on controllers, and real-time control in networked environments. Seven research problems are identified from these areas for investigation in this thesis, and accordingly seven major contributions have been claimed. Timing behaviour, quality of control, and integrated design for real-time control systems are highlighted throughout this thesis. In control design, a model-free control technique, pattern predictive control, is developed for complex reactive distillation processes. Alleviating the requirement of accurate process models, the developed control technique integrates pattern recognition, fuzzy logic, non-linear transformation, and predictive control into a unified framework to solve complex problems. Characterising the QoC indirectly with control latency and jitter, scheduling strategies for multiple control tasks are proposed to minimise the latency and/or jitter. Also, a hierarchical, QoC driven, and event-triggering feedback scheduling architecture is developed with plug-ins of either the earliest-deadline-first or fixed priority scheduling. Linking to the QoC directly, the architecture minimises the use of computing resources without sacrifice of the system QoC. It considers the control requirements, but does not rely on the control design. For real-time NCS, the dynamics of the network delay are analysed first, and the nonuniform distribution and multi-fractal nature of the delay are revealed. These results do not support two fundamental assumptions used in existing NCS literature. Then, considering the control requirements, solutions are provided to the challenging NCS problems from the network perspective. To compensate for the network delay, a real-time queuing protocol is developed to smooth out the time-varying delay and thus to achieve more predictable behaviour of packet transmissions. For control packet dropout, simple yet effective compensators are proposed. Finally, combining the queuing protocol, the packet loss compensation, the configuration of the worst-case communication delay, and the control design, an integrated design framework is developed for real-time NCS. With this framework, the network delay is limited to within a single control period, leading to simplified system analysis and improved QoC

    A Pseudo-Linear Time Algorithm for the Optimal Discrete Speed Minimizing Energy Consumption

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    International audienceWe consider the classical problem of minimizing off-line the total energy consumption required to execute a set of n real-time jobs on a single processor with a finite number of available speeds. Each real-time job is defined by its release time, size, and deadline (all bounded integers). The goal is to find a processor speed schedule, such that no job misses its deadline and the energy consumption is minimal. We propose a pseudo-linear time algorithm that checks the schedulability of the given set of n jobs and computes an optimal speed schedule. The time complexity of our algorithm is in O(n), to be compared with O(nlog(n)) for the best known solution. Besides the complexity gain, the main interest of our algorithm is that it is based on a completely different idea: instead of computing the critical intervals, it sweeps the set of jobs and uses a dynamic programming approach to compute an optimal speed schedule. Our linear time algorithm is still valid (with some changes) when arbitrary (non-convex) power functions and when switching costs are taken into account

    Power, Energy, and Thermal Management for Clustered Manycores

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    Efficient and effective system-level power, energy, and thermal management are very important issues in modern computing systems, for which clustered architectures with multiple voltage islands are an expected compromise between global and per-core DVFS. In this dissertation, we focus on two of the most relevant problems for such architectures, specifically, optimizing performance under power/thermal constraints, and minimizing energy under performance constraints
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