Multicore thermal management using approximate explicit model predictive control

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.

Published in:
Proceedings of 2010 IEEE International Symposium on Circuits and Systems, 3321-3324
Presented at:
IEEE International Symposium on Circuits and Systems - ISCAS 2010, Paris, France, 30 05 - 2 06 2010

Note: The status of this file is: Anyone
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 Record created 2011-10-24, last modified 2020-07-30

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