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Vectorization of local search for solving flow-shop scheduling problem on Xeon Phi™ MIC co-processors

Vaillant Gautier 1, 2 Mohand Mezmaz 1 Daniel Tuyttens 1 Nouredine Melab 2
2 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
Abstract : This paper aims to propose a vectorizable cost function for the permutation flow-shop problem (PFSP) with the makespan criterion. This vectorization has been tested on a Xeon Phi core, using a local search. Indeed, Xeon Phi co-processors require vectorization in order to get the best performance from the device. Taillard's benchmark instances are used for the validation of the algorithm. The obtained results show that vectorization is more efficient as the number of jobs and the number of machines increase. Speedups up to 4.5× are recorded.
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https://hal.inria.fr/hal-01419077
Contributor : Nouredine Melab <>
Submitted on : Sunday, December 18, 2016 - 3:30:41 PM
Last modification on : Thursday, February 21, 2019 - 10:52:49 AM

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Vaillant Gautier, Mohand Mezmaz, Daniel Tuyttens, Nouredine Melab. Vectorization of local search for solving flow-shop scheduling problem on Xeon Phi™ MIC co-processors. 2016 International Conference on High Performance Computing & Simulation (HPCS), Jul 2016, Innsbruck, Austria. ⟨10.1109/HPCSim.2016.7568407⟩. ⟨hal-01419077⟩

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