Reducing thread divergence in GPU-based b&b applied to the flow-shop problem

Authors:
Imen Chakroun;Ahcène Bendjoudi;Nouredine Melab
Affiliations:
Université Lille 1 CNRS/LIFL, INRIA Lille Nord Europe, Cité scientifique, Villeneuve d'Ascq cedex, France;Division Théorie et Ingénierie des Systèmes Informatiques DTISI, CEntre de Recherche sur l'Information Scientifique et Technique (CERIST), Ben-Aknoun, Algiers, Algeria;Université Lille 1 CNRS/LIFL, INRIA Lille Nord Europe, Cité scientifique, Villeneuve d'Ascq cedex, France
Venue:
PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part I
Year:
2011

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Abstract

In this paper, we propose a pioneering work on designing and programming B&B algorithms on GPU. To the best of our knowledge, no contribution has been proposed to raise such challenge. We focus on the parallel evaluation of the bounds for the Flow-shop scheduling problem. To deal with thread divergence caused by the bounding operation, we investigate two software based approaches called thread data reordering and branch refactoring. Experiments reported that parallel evaluation of bounds speeds up execution up to 54.5 times compared to a CPU version.