Title :

A performance-oriented comparative study of the Chapel high-productivity language to conventional programming environments

Author(s) :

Helbecque, Guillaume [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Gmys, Jan [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Carneiro, Tiago [Auteur]
Université du Luxembourg [Uni.lu]
Melab, Nouredine [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Optimisation de grande taille et calcul large échelle [BONUS]
Bouvry, Pascal [Auteur]
Université du Luxembourg [Uni.lu]

Conference title :

13th International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM'22)

City :

Séoul

Country :

Corée du Sud

Start date of the conference :

2022-04-02

Book title :

PMAM '22: Proceedings of the Thirteenth International Workshop on Programming Models and Applications for Multicores and Manycores

Publication date :

2022-04-18

English keyword(s) :

Chapel
MPI
Multi-core
OpenMP
Parallel computing
Productivity-awareness

HAL domain(s) :

Informatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
Informatique [cs]/Langage de programmation [cs.PL]

English abstract : [en]

The increase in complexity, diversity and scale of high performance computing environments, as well as the increasing sophistication of parallel applications and algorithms call for productivity-aware programming languages ...
Show more >The increase in complexity, diversity and scale of high performance computing environments, as well as the increasing sophistication of parallel applications and algorithms call for productivity-aware programming languages for high-performance computing. Among them, the Chapel programming language stands out as one of the more successful approaches based on the Partitioned Global Address Space programming model. Although Chapel is designed for productive parallel computing at scale, the question of its competitiveness with well-established conventional parallel programming environments arises. To this end, this work compares the performance of Chapel-based fractal generation on shared-and distributed-memory platforms with corresponding OpenMP and MPI+X implementations. The parallel computation of the Mandelbrot set is chosen as a test-case for its high degree of parallelism and its irregular workload. Experiments are performed on a cluster composed of 192 cores using the French national testbed Grid'5000. Chapel as well as its default tasking layer demonstrate high performance in shared-memory context, while Chapel competes with hybrid MPI+OpenMP in distributed-memory environment.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