GPU-based Multi-start Local Search Algorithms

Luong, Thé Van; Melab, Nouredine; Talbi, El-Ghazali

Type de document :

Communication dans un congrès avec actes

Titre :

GPU-based Multi-start Local Search Algorithms

Auteur(s) :

Luong, Thé Van [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Melab, Nouredine [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Talbi, El-Ghazali [Auteur]

Parallel Cooperative Multi-criteria Optimization [DOLPHIN]

Éditeur(s) ou directeur(s) scientifique(s) :

Carlos A. Coello Coello

Titre de la manifestation scientifique :

Learning and Intelligent Optimization

Ville :

Rome

Pays :

Italie

Date de début de la manifestation scientifique :

2011

Titre de la revue :

Lecture Notes in Computer Science

Éditeur :

Springer

Date de publication :

2011

Discipline(s) HAL :

Sciences cognitives/Informatique

Résumé en anglais : [en]

In practice, combinatorial optimization problems are complex and computationally time-intensive. Local search algorithms are powerful heuristics which allow to significantly reduce the computation time cost of the solution ...
Lire la suite >In practice, combinatorial optimization problems are complex and computationally time-intensive. Local search algorithms are powerful heuristics which allow to significantly reduce the computation time cost of the solution exploration space. In these algorithms, the multi-start model may improve the quality and the robustness of the obtained solutions. However, solving large size and time-intensive optimization problems with this model requires a large amount of computational resources. GPU computing is recently revealed as a powerful way to harness these resources. In this paper, the focus is on the multi-start model for local search algorithms on GPU. We address its re-design, implementation and associated issues related to the GPU execution context. The preliminary results demonstrate the effectiveness of the proposed approaches and their capabilities to exploit the GPU architecture.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

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

Source :

Harvested from HAL

Fichiers

https://hal.inria.fr/inria-00638813/document
Accès libre
Accéder au document

https://hal.inria.fr/inria-00638813/document
Accès libre
Accéder au document

document
Accès libre
Accéder au document

LION5.pdf
Accès libre
Accéder au document

document
Accès libre
Accéder au document

LION5.pdf
Accès libre
Accéder au document

GPU-based Multi-start Local Search Algorithms BibTeX CSV Excel RIS

Fichiers

GPU-based Multi-start Local Search Algorithms

BibTeX

CSV

Excel

RIS