Investigating Portability in Chapel for Tree-based Optimization on GPU-powered Clusters

Carneiro, Tiago; Kayraklioglu, Engin; Helbecque, Guillaume; Melab, Nouredine

Document type :

Communication dans un congrès avec actes

DOI :

10.1007/978-3-031-69583-4_27

Title :

Investigating Portability in Chapel for Tree-based Optimization on GPU-powered Clusters

Author(s) :

Carneiro, Tiago [Auteur]
IMEC [IMEC]
Kayraklioglu, Engin [Auteur]
Hewlett Packard Enterprise (Hewlett Packard) [HPE]
Helbecque, Guillaume [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Inria Lille - Nord Europe
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Université de Lille
Université du Luxembourg = University of Luxembourg = Universität Luxemburg [uni.lu]
Melab, Nouredine [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Inria Lille - Nord Europe
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Université de Lille

Conference title :

30th International European Conference on Parallel and Distributed Computing

City :

Madrid

Country :

Espagne

Start date of the conference :

2024-08-26

Book title :

Euro-Par 2024: Parallel Processing

Publication place :

Cham

Publication date :

2024-08-26

English keyword(s) :

GPU Computing
Backtracking
Chapel
Portability

HAL domain(s) :

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

English abstract : [en]

The Top500 list features supercomputers powered by accelerators from different vendors. This variety brings, along with the heterogeneity challenge, both the code and performance portability challenges. In this context, ...
Show more >The Top500 list features supercomputers powered by accelerators from different vendors. This variety brings, along with the heterogeneity challenge, both the code and performance portability challenges. In this context, Chapel's native GPU support comes as a solution for code portability between different vendors. In this paper, we investigate the viability of using the Chapel high-productivity language as a tool to achieve both code and performance portability in large-scale tree-based search. As a case study, we implemented a distributed backtracking for solving permutation combinatorial problems. Extensive experiments conducted on big N-Queens problem instances, using up to 512 NVIDIA GPUs and 1024 AMD GPUs on Top500 supercomputers, reveal that it is possible to scale on the two different systems using the same tree-based search written in Chapel. This trade-off results in a performance decrease of less than 10% for the biggest problem instances.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

Calcul ultra-scale pour la résolution de problèmes d'optimisation de grande taille

Collections :

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

Source :

Harvested from HAL

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