A comparative study of high-productivity ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
A comparative study of high-productivity high-performance programming languages for parallel metaheuristics
Auteur(s) :
Gmys, Jan [Auteur correspondant]
University of Mons [Belgium] [UMONS]
Carneiro, Tiago [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Melab, Nouredine [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Talbi, El-Ghazali [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Tuyttens, Daniel [Auteur]
University of Mons [Belgium] [UMONS]
University of Mons [Belgium] [UMONS]
Carneiro, Tiago [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Melab, Nouredine [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Talbi, El-Ghazali [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Tuyttens, Daniel [Auteur]
University of Mons [Belgium] [UMONS]
Titre de la revue :
Swarm and Evolutionary Computation
Éditeur :
Elsevier
Date de publication :
2020-06-09
ISSN :
2210-6502
Mot(s)-clé(s) en anglais :
Metaheuristics
Parallel metaheuristics
High-productivity languages
Parallel computing
Parallel metaheuristics
High-productivity languages
Parallel computing
Discipline(s) HAL :
Informatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
Informatique [cs]/Algorithme et structure de données [cs.DS]
Informatique [cs]/Recherche opérationnelle [cs.RO]
Informatique [cs]/Algorithme et structure de données [cs.DS]
Informatique [cs]/Recherche opérationnelle [cs.RO]
Résumé en anglais : [en]
Parallel metaheuristics require programming languages that provide both, high performance and a high level of programmability. This paper aims at providing a useful data point to help practitioners gauge the difficult ...
Lire la suite >Parallel metaheuristics require programming languages that provide both, high performance and a high level of programmability. This paper aims at providing a useful data point to help practitioners gauge the difficult question of whether to invest time and effort into learning and using a new programming language. To accomplish this objective, three productivity-aware languages (Chapel, Julia, and Python) are compared in terms of performance, scalability and productivity. To the best of our knowledge, this is the first time such a comparison is performed in the context of parallel metaheuristics. As a test-case, we implement two parallel metaheuristics in three languages for solving the 3D Quadratic Assignment Problem (Q3AP), using thread-based parallelism on a multi-core shared-memory computer. We also evaluate and compare the performance of the three languages for a parallel fitness evaluation loop, using four different test-functions with different computational characteristics. Besides providing a comparative study, we give feedback on the implementation and parallelization process in each language.Lire moins >
Lire la suite >Parallel metaheuristics require programming languages that provide both, high performance and a high level of programmability. This paper aims at providing a useful data point to help practitioners gauge the difficult question of whether to invest time and effort into learning and using a new programming language. To accomplish this objective, three productivity-aware languages (Chapel, Julia, and Python) are compared in terms of performance, scalability and productivity. To the best of our knowledge, this is the first time such a comparison is performed in the context of parallel metaheuristics. As a test-case, we implement two parallel metaheuristics in three languages for solving the 3D Quadratic Assignment Problem (Q3AP), using thread-based parallelism on a multi-core shared-memory computer. We also evaluate and compare the performance of the three languages for a parallel fitness evaluation loop, using four different test-functions with different computational characteristics. Besides providing a comparative study, we give feedback on the implementation and parallelization process in each language.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
Source :
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