Title :

A GPU-accelerated Branch-and-Bound Algorithm for the Flow-Shop Scheduling Problem

Author(s) :

Melab, Nouredine [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Chakroun, Imen [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Mezmaz, Mohand [Auteur]
Institut de Mathématiques [Mons]
Tuyttens, Daniel [Auteur]
Institut de Mathématiques [Mons]

Conference title :

14th IEEE International Conference on Cluster Computing, Cluster'12

City :

Beijin

Country :

Chine

Start date of the conference :

2012-09-24

Publication date :

2012-09-24

English keyword(s) :

Flow-Shop Scheduling
Massively Parallel Computing
GPU Computing
Branch-and-Bound Algorithms
Lower Bounding
Flow-Shop Scheduling.

HAL domain(s) :

Informatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]

English abstract : [en]

Branch-and-Bound (B&B) algorithms are time intensive tree-based exploration methods for solving to optimality combinatorial optimization problems. In this paper, we investigate the use of GPU computing as a major complementary ...
Show more >Branch-and-Bound (B&B) algorithms are time intensive tree-based exploration methods for solving to optimality combinatorial optimization problems. In this paper, we investigate the use of GPU computing as a major complementary way to speed up those methods. The focus is put on the bounding mechanism of B&B algorithms, which is the most time consuming part of their exploration process. We propose a parallel B&B algorithm based on a GPU-accelerated bounding model. The proposed approach concentrate on optimizing data access management to further improve the performance of the bounding mechanism which uses large and intermediate data sets that do not completely fit in GPU memory. Extensive experiments of the contribution have been carried out on well known FSP benchmarks using an Nvidia Tesla C2050 GPU card. We compared the obtained performances to a single and a multithreaded CPU-based execution. Accelerations up to x100 are achieved for large problem instances.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL