Scheduling on power-heterogeneous processors

Susanne Albers 1 Evripidis Bampis 2 Dimitrios Letsios 3 Giorgio Lucarelli 4 Richard Stotz 1
2 RO - Recherche Opérationnelle
LIP6 - Laboratoire d'Informatique de Paris 6
3 COATI - Combinatorics, Optimization and Algorithms for Telecommunications
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - COMRED - COMmunications, Réseaux, systèmes Embarqués et Distribués
4 DATAMOVE - Data Aware Large Scale Computing
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : We consider the problem of scheduling a set of jobs, each one specified by its release date, its deadline and its processing volume, on a set of heterogeneous speed-scalable processors, where the energy-consumption rate is processor-dependent. Our objective is to minimize the total energy consumption when both the preemption and the migration of jobs are allowed. We propose a new algorithm based on a compact linear programming formulation. Our method approaches the value of the optimal solution within any desired accuracy for a large set of continuous power functions. Furthermore, we develop a faster combinatorial algorithm based on flows for standard power functions and jobs whose density is lower bounded by a small constant. Finally, we extend and analyze the AVerage Rate (AVR) online algorithm in the heterogeneous setting.
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Susanne Albers, Evripidis Bampis, Dimitrios Letsios, Giorgio Lucarelli, Richard Stotz. Scheduling on power-heterogeneous processors. Information and Computation, Elsevier, 2017, 257, pp.22-33. ⟨10.1016/j.ic.2017.09.013⟩. ⟨hal-01668736⟩

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