Online Thermal Control Methods for Multi-Processor Systems

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.

Multicore thermal management using approximate explicit Model Predictive Control

David Atienza Alonso, Giovanni De Micheli, Colin Neil Jones, Francesco Zanini

Meeting temperature constraints and reducing the hot-spots are critical for achieving reliable and efficient operation of complex multi-core systems. In this paper 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 optimization problem considers the thermal profile of the system, its evolution over time and current time-varying workload requirements. We formulate this problem as a discrete-time control problem using model predictive control. The solution is computed off-line and partially on-line using an explicit approximate algorithm. This proposed method, compared with the optimum approach provides a significant reduction in hardware requirements and computational cost at the expense of a small loss in accuracy. We perform experiments on a model of the 8-core Niagara-1 multicore architecture using benchmarks ranging from web-accessing to playing multimedia. Results show that the proposed method provides comparable performance( loss up to 2.7%) versus the optimum solution with a reduction up to 72.5x in the the computational complexity.

IEEE Press2010

Multicore thermal management using approximate explicit model predictive control

David Atienza Alonso, Giovanni De Micheli, Colin Neil Jones, Francesco Zanini

Meeting temperature constraints and reducing the hot-spots are critical for achieving reliable and efficient operation of complex multi-core systems. In this paper 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 optimization problem considers the thermal profile of the system, its evolution over time and current time- varying workload requirements. We formulate this problem as a discrete-time control problem using model predictive control. The solution is computed off-line and partially on-line using an explicit approximate algorithm. This proposed method, compared with the optimum approach provides a significant reduction in hardware requirements and computational cost at the expense of a small loss in accuracy. We perform experiments on a model of the 8-core Niagara-1 multicore architecture using benchmarks ranging from web-accessing to playing multimedia. Results show that the proposed method provides comparable performance(loss up to 2.7%) versus the optimum solution with a reduction up to 72.5× in the the computational complexity.

IEEE2010

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

Mohamed Mostafa Sabry Aly, David Atienza Alonso, Giovanni De Micheli, Francesco Zanini

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.

2011