104 research outputs found

    Online Convex Optimization-Based Algorithm for Thermal Management of MPSoCs

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    Meeting the temperature constraints and reducing the hot-spots are critical for achieving reliable and efficient operation of complex multi-core systems. The goal of thermal management is to meet maximum operating temperature constraints, while tracking timevarying performance requirements. Current approaches avoid thermal violations by forcing abrupt operating points changes, which cause sharp performance degradation. In this paper we aim at achieving an online smooth thermal control action, that minimizes the tracking error. We formulate this problem as a discrete-time optimal control problem, which can be solved via online by using an embedded convex optimization solver using a receding horizon approach. The optimization problem considers the thermal profile of the system, its evolution over time, current and past time-varying workload requirements. We perform experiments on a model of the 8-core Niagara-1 multicore architecture, which show that the proposed method outperforms state-of-the-art thermal management approaches by enabling performance speed-ups of up to 2:5ÂŁ and improvements up to 12x and 3.4x in relation to frequency and temperature variations over time, respectively

    DeadPool: Performance Deadline Based Frequency Pooling and Thermal Management Agent in DVFS Enabled MPSoCs

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    High operating temperature and frequent thermal cycles in a multi-processor system-on-chip, which is now popularly utilized in mobile/Edge devices, harm the overall lifespan and reliability of such devices. In this paper, we propose an intelligent software agent that works alongside other resource mapping and partitioning mechanism in order to monitor and reduce the operating temperature of the system by regulating the operating frequency of the CPU cores while catering for performance constraint at the same time. Our proposed approach?, DeadPool thermal management agent, is able to reduce the overall operating temperature of the system by 24.21% and reduce thermal cycle by 67.42% at the most when compared to the state-of-the-art methods

    Convex-Based Thermal Management for 3D MPSoCs Using DVFS and Variable-Flow Liquid Cooling

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    In this work, we propose a novel online thermal management approach based on model predictive control for 3D multi-processors system on chip (MPSoCs) using microfluidic cooling. The controller uses dynamic voltage and frequency scaling (DVFS) for the computational cores and adjusts the liquid flow rate to meet the desired performance requirements and to minimize the overall MPSoC energy consumption (MPSoC power consumption+cooling power consumption). Our experimental results illustrate that our policy satisfies performance requirements and maintains the temperature below the specified threshold, while reducing cooling energy by up to 50% compared with traditional state-of-the-art liquid cooling techniques. The proposed policy also keeps the thermal profile up to 18°C lower compared with state of the art 3D thermal management using variable-flow liquid cooling

    Online Thermal Control Methods for Multi-Processor Systems

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    With technological advances, the number of cores integrated on a chip is increasing. This, in turn is leading to thermal constraints and thermal design challenges. Temperature gradients and hot-spots not only affect the performance of the system, but also lead to unreliable circuit operation and affect the life-time of the chip. Meeting temperature constraints and reducing hot-spots are critical for achieving reliable and efficient operation of complex multi-core systems. In this article we analyze the use of four of the most promising families of online control techniques for thermal management of multi-processors system-on-chip (MPSoC). In particular, in our exploration we aim at achieving an online smooth thermal control action that minimizes the performance loss as well as the computational and hardware overhead of embedding a thermal management system inside the MPSoC. The definition of the optimization problem to tackle in this work considers the thermal profile of the system, its evolution over time and current time-varying workload requirements. Thus, this problem is formulated as a finite-horizon optimal control problem and we analyze the control features of different on-line thermal control approaches. In addition, we implemented the policies on an MPSoC hardware simulation platform and performed experiments on a cycle-accurate model of the 8-core Niagara multi-core architecture using benchmarks ranging from web-accessing to playing multimedia. Results show different trade-offs among the analyzed techniques regarding the thermal profile, the frequency setting, the power consumption and the implementation complexity

    Design of Thermal Management Control Policies for Multiprocessors Systems on Chip

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    The contribution of this thesis is a thorough study of thermal aware policy design for MPSoCs. The study includes the modelling of their thermal behavior as well as the improvement and the definition of new thermal management and balancing policies. The work is structured on three main specific disciplines. The areas of contributions are: modeling, algorithms and system design. This thesis extends the field of modeling by proposing new techniques to represent the thermal behavior of MPSoCs using a mathematical formalization. Heat transfer and modelling of physical properties of MPSoCs have been extensively studied. Special emphasis is given to the way the system cools down (i.e. micro-cooling, natural heat dissipation etc.) and the heat propagates inside the MPSoC. The second contribution of this work is related to policies, which manage MPSoC working frequencies and micro-cooling pumps to satisfy user requirements in the most effective possible way, while consuming the lowest possible amount of resources. Several families of thermal policies algorithms have been studied and analyzed in this work for both 2D and 3D MPSoCs including liquid cooling technologies. The discipline of system design has also been extended during the development of this thesis. Thermal management policies have been implemented in real emulation platforms and contributions in this area are related to the design and implementation of proposed innovations in real MPSoC platforms

    Hierarchical Thermal Management Policy for High-Performance 3D Systems with Liquid Cooling

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    3-Dimensional integrated circuits and systems are expected to be present in electronic products in the short term. We consider specifically 3-D multi-processor systems-onchip (MPSoCs), realized by stacking silicon CMOS chips and interconnecting them by means of through-silicon vias (TSVs). Because of the high power density of devices and interconnect in the 3D stack, thermal issues pose critical challenges, such as hot-spot avoidance and thermal gradient reduction. Thermal management is achieved by a combination of active control of on-chip switching rates as well as active interlayer cooling with pressurized fluids. In this paper, we propose a novel online thermal management policy for high-performance 3D systems with liquid cooling. Our proposed controller uses a hierarchical approach with a global controller regulating the active cooling and local controllers (on each layer) performing dynamic voltage and frequency scaling (DVFS) and interacting with the global controller. Then, the online control is achieved by policies that are computed off-line by solving an optimization problem that considers the thermal profile of 3D-MPSoCs, its evolution over time and current time-varying workload requirements. The proposed hierarchical scheme is scalable to complex (and heterogeneous) 3D chip stacks. We perform experiments on a 3D-MPSoC case study with different interlayer cooling structures, using benchmarks ranging from web-accessing to playing multimedia. Results show significant advantages in terms of energy savings that reaches values up to 50% versus state-of-the-art thermal control techniques for liquid cooling, and thermal balance with differences of less than 10oC per layer

    Thermal-Aware System-Level Modeling and Management for Multi-Processor Systems-on-Chip

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    Multi-Processor Systems-on-Chip (MPSoCs) are penetrating the electronics market as a powerful, yet commercially viable, solution to answer the strong and steadily growing demand for scalable and high performance systems, at limited design complexity. However, it is critical to develop dedicated system-level design methodologies for multi-core architectures that seamlessly address their thermal modeling, analysis and management. In this work, we first formulate the problem of system-level thermal modeling and link it to produce a global thermal management formulation as a discrete-time optimal control problem, which can be solved using finite-horizon model-predictive control (MPC) techniques, while adapting to the actual time-varying unbalanced MPSoC workload requirements. Finally, we compare the system-level MPC-based thermal modeling and management approaches on an industrial 8-core MPSoC design and show their different trade-offs regarding performance while respecting operating temperature bounds

    A Survey and Comparative Study of Hard and Soft Real-time Dynamic Resource Allocation Strategies for Multi/Many-core Systems

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    Multi-/many-core systems are envisioned to satisfy the ever-increasing performance requirements of complex applications in various domains such as embedded and high-performance computing. Such systems need to cater to increasingly dynamic workloads, requiring efficient dynamic resource allocation strategies to satisfy hard or soft real-time constraints. This article provides an extensive survey of hard and soft real-time dynamic resource allocation strategies proposed since the mid-1990s and highlights the emerging trends for multi-/many-core systems. The survey covers a taxonomy of the resource allocation strategies and considers their various optimization objectives, which have been used to provide comprehensive comparison. The strategies employ various principles, such as market and biological concepts, to perform the optimizations. The trend followed by the resource allocation strategies, open research challenges, and likely emerging research directions have also been provided
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