HB&B@GRID: An heterogeneous grid-enabled ...
Type de document :
Communication dans un congrès avec actes
Titre :
HB&B@GRID: An heterogeneous grid-enabled Branch and Bound algorithm
Auteur(s) :
Chakroun, Imen [Auteur]
IMEC [IMEC]
Melab, Nouredine [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
IMEC [IMEC]
Melab, Nouredine [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Titre de la manifestation scientifique :
2016 International Conference on High Performance Computing & Simulation (HPCS)
Ville :
Innsbruck
Pays :
Autriche
Date de début de la manifestation scientifique :
2016-07-18
Titre de l’ouvrage :
IEEE
Date de publication :
2016-09-15
Mot(s)-clé(s) en anglais :
GPU
Branch and Bound
heterogeneous resources
distributed computing
master-slave
Branch and Bound
heterogeneous resources
distributed computing
master-slave
Discipline(s) HAL :
Informatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
Résumé en anglais : [en]
In this paper, we propose an extended version of the hybrid multi-core and GPU-accelerated Branch-and-Bound (B&B) algorithm previously introduced for massively-parallel distributed and heterogeneous environments. The ...
Lire la suite >In this paper, we propose an extended version of the hybrid multi-core and GPU-accelerated Branch-and-Bound (B&B) algorithm previously introduced for massively-parallel distributed and heterogeneous environments. The proposed algorithm consists in hierarchically combining two levels of parallelism by (1) dividing the B&B tree exploration among multiple distributed resources using the B&B@GRID approach, and (2) exploring in parallel each sub-tree using an heterogeneous meta-algorithm. Using this portable, heterogeneous and self-adaptive approach allows to achieve high performance.Lire moins >
Lire la suite >In this paper, we propose an extended version of the hybrid multi-core and GPU-accelerated Branch-and-Bound (B&B) algorithm previously introduced for massively-parallel distributed and heterogeneous environments. The proposed algorithm consists in hierarchically combining two levels of parallelism by (1) dividing the B&B tree exploration among multiple distributed resources using the B&B@GRID approach, and (2) exploring in parallel each sub-tree using an heterogeneous meta-algorithm. Using this portable, heterogeneous and self-adaptive approach allows to achieve high performance.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :