Convergence Analysis of Run-Time Distributed Optimization on Adaptive Systems Using Game Theory - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier
Conference Papers Year : 2008

Convergence Analysis of Run-Time Distributed Optimization on Adaptive Systems Using Game Theory

Abstract

We consider multiprocessor system-on-chip (MP-SoC) integrating several processing elements (PE). These architectures require distributed and scalable control techniques for run-time optimization of applicative parameters. Our approach is to use the game theory as an optimization model to solve the trade-off issues at run-time. We applied it to the distributed dynamic voltage frequency scaling (DVFS) management, adjusting at run-time the frequency set of each PE based on the synchronization between tasks of the application graph and the PE temperature profile. Results show that the analyzed algorithm converges to a solution in about 94% of the cases and in less than 40 calculation cycles for a 100-processor MP-SoC. It reaches an average optimization of 89% compared to an off-line centralized reference but about 140 times faster when simulating.
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Dates and versions

lirmm-00326533 , version 1 (03-10-2008)

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Cite

Diego Puschini, Fabien Clermidy, Pascal Benoit, Gilles Sassatelli, Lionel Torres. Convergence Analysis of Run-Time Distributed Optimization on Adaptive Systems Using Game Theory. FPL'08: International Conference on Field Programmable Logic and Applications, Sep 2008, Heidelberg, Germany. pp.555-558, ⟨10.1109/FPL.2008.4630007⟩. ⟨lirmm-00326533⟩
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