Massively Parallel Asynchronous Fractal ...
Type de document :
Communication dans un congrès avec actes
Titre :
Massively Parallel Asynchronous Fractal Optimization
Auteur(s) :
Firmin, Thomas [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Université de Lille
Talbi, El-Ghazali [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Université de Lille
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Inria Lille - Nord Europe
Optimisation de grande taille et calcul large échelle [BONUS]
Université de Lille
Talbi, El-Ghazali [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Université de Lille
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Inria Lille - Nord Europe
Titre de la manifestation scientifique :
2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
Ville :
St. Petersburg
Pays :
France
Date de début de la manifestation scientifique :
2023-05-15
Éditeur :
IEEE
Mot(s)-clé(s) en anglais :
Fractal optimization
Discipline(s) HAL :
Informatique [cs]
Résumé en anglais : [en]
Fractal-based decomposition is a flexible framework representing a family of optimization algorithms based on a hierarchical decomposition of the search space. We have built a software called Zellij, in which we were able ...
Lire la suite >Fractal-based decomposition is a flexible framework representing a family of optimization algorithms based on a hierarchical decomposition of the search space. We have built a software called Zellij, in which we were able to instantiate popular decomposition-based algorithms. Our goal is to tackle optimization problems characterized by computationally expensive objective functions and high dimensional search space. In this paper, we propose a generic asynchronous parallel methodology of fractal-based optimization algorithms on multi-nodes and multi-CPUs distributed environments. Experimental results show a significantly reduced computation time between the mono-threaded version and the asynchronous one. The obtained results are also analyzed according to the various search components such as tree search, exploration, and exploitation strategies.Lire moins >
Lire la suite >Fractal-based decomposition is a flexible framework representing a family of optimization algorithms based on a hierarchical decomposition of the search space. We have built a software called Zellij, in which we were able to instantiate popular decomposition-based algorithms. Our goal is to tackle optimization problems characterized by computationally expensive objective functions and high dimensional search space. In this paper, we propose a generic asynchronous parallel methodology of fractal-based optimization algorithms on multi-nodes and multi-CPUs distributed environments. Experimental results show a significantly reduced computation time between the mono-threaded version and the asynchronous one. The obtained results are also analyzed according to the various search components such as tree search, exploration, and exploitation strategies.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Projet ANR :
Collections :
Source :