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Energy-aware Partial-Duplication Task Mapping under Real-Time and Reliability Constraints

Abstract : An efficient task execution on multicore platforms can lead to low energy consumption. To achieve that, an Integer Non-Linear Programming (INLP) formulation is proposed that performs task mapping by jointly addressing task allocation, task frequency assignment, and task duplication. The goal is to minimize energy consumption under real-time and reliability constraints. To provide an optimal solution, the original INLP problem is safely transformed to an equivalent Mixed Integer Linear Programming (MILP) problem. The comparison of the proposed approach with existing energy-aware task mapping approaches shows that the proposed approach is able to find solutions when other approaches fail, achieving an overall lower energy consumption.
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https://hal.inria.fr/hal-02927474
Contributor : Kritikakou Angeliki <>
Submitted on : Friday, January 29, 2021 - 4:53:18 PM
Last modification on : Tuesday, February 2, 2021 - 3:33:36 AM

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  • HAL Id : hal-02927474, version 1

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Minyu Cui, Lei Mo, Angeliki Kritikakou, Emmanuel Casseau. Energy-aware Partial-Duplication Task Mapping under Real-Time and Reliability Constraints. SAMOS 2020 - International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation, Jul 2020, Samos / Virtual, Greece. ⟨hal-02927474⟩

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