A Strategy for the Parallel Implementations of Stochastic Lagrangian Methods - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Rapport (Rapport De Recherche) Année : 2014

A Strategy for the Parallel Implementations of Stochastic Lagrangian Methods

Résumé

In this paper, we present some investigations on the parallelization of a stochastic Lagrangian simulation. For the self sufficiency of this work, we start by recalling the stochastic methods used to solve Parabolic Partial Differential Equations with a few physical remarks. Then, we exhibit different object-oriented ideas for such methods. In order to clearly illustrate these ideas, we give an overview of the library PALMTREE that we developed. After these considerations, we discuss the importance of the management of random numbers and argue for the choice of a particular strategy. To support our point, we show some numerical experiments of this approach, and display a speedup curve of PALMTREE. Then, we discuss the problem in managing the parallelization scheme. Finally, we analyze the parallelization of hybrid simulation for a system of Partial Differential Equations. We use some works done in hydrogeology to demonstrate the power of such a concept to avoid numerical diffusion in the solution of Fokker-Planck Equations and investigate the problem of parallelizing scheme under the constraint entailed by domain decomposition. We conclude with a presentation of the latest design that was created for PALMTREE and give a sketch of the possible work to get a powerful parallelized scheme.
Fichier principal
Vignette du fichier
Mcqmc_version_hal.pdf (157.78 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01066410 , version 1 (19-09-2014)
hal-01066410 , version 2 (30-06-2015)
hal-01066410 , version 3 (25-11-2015)

Identifiants

  • HAL Id : hal-01066410 , version 1

Citer

Lionel Lenôtre. A Strategy for the Parallel Implementations of Stochastic Lagrangian Methods. [Research Report] Inria. 2014. ⟨hal-01066410v1⟩
607 Consultations
393 Téléchargements

Partager

Gmail Facebook X LinkedIn More