Reducing Thread Divergence in GPU-based B&B Applied to the Flow-shop problem

Chakroun, Imen; Bendjoudi, Ahcène; Melab, Nouredine

Reducing Thread Divergence in GPU-based B&B Applied to the Flow-shop problem

Date

2011-09-11

Authors

Chakroun, Imen

Bendjoudi, Ahcène

Melab, Nouredine

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.

Keywords

Branch and Bound, Data Parallelism, GPU Computing, Thread Divergence, Flow-shop Scheduling

URI

http://dl.cerist.dz/handle/CERIST/195

Collections

International Conference Papers

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