Parallel Unstructured Mesh Adaptation Based on Iterative Remershing and Repartitioning

International audienceWe present a parallel unstructured mesh adaptation algorithm based on iterative remeshing and mesh repartitioning. The algorithm rests on a two-level parallelization scheme allowing to tweak the mesh group size for remeshing, and on a mesh repartitioning scheme based on interface displacement by front advancement. The numerical procedure is implemented in the open source ParMmg software package. It enables the reuse of existing sequential remeshing libraries, a non-intrusive linkage with thirdparty solvers, and a tunable exploitation of distributed parallel environments. We show the efficiency of the approach by comparing interface displacement repartitioning with graph-based repartitioning, and by showing isotropic weak-scaling tests and preliminary anisotropic tests

Modular FEM framework "ModFem" for generic scientific parallel simulations

We present the design and its' implementation for a flexible and robust parallel modular finite element (FEM) framework, called ModFem. The design is based on reusable modules which use narrow and well-defined interfaces to cooperate. At the top of the architecture there are problem dependent modules. Problem dependent modules can be additionally grouped together by "super-modules". This structure allows for applying the sequential codes to parallel environments and also support solving multi-physics and multi-scale problems

Remaillage parallèle rapide pour les simulations de grands écoulements (LES) sur des maillages de très grande taille

Numerical simulations on very large meshes, such as large-addy simulations (LES), cannot be performed without resorting to distributed-memory parallelism. For these methods, a sufficient precision can only be achieved by remeshing dynamically the areas that need it. Such a remeshing must therefore be performed in parallel.This paper presents the coarse-grain parallel remeshing method which has been devised and implemented in the PaMPA library for handling distributed meshes in parallel. This method is validated in the context of an industrial LES simulation on a helicopter turbine combustion chamber, on a mesh of more than one billion elements.Les simulations numériques portant sur des maillages de très grande taille, telles que les méthodes LES ("large-eddy simulations"), ne peuvent être réalisées qu'en ayant recours au parallélisme à mémoire distribuée. Pour ces méthodes, une précision suffisante ne peut être atteinte qu'en remaillant dynamiquement les zones qui le nécessitent. Ce remaillage doit donc être effectué en parallèle.Cet article présente la méthode de remaillage parallèle à gros grain conçue et mise en œuvre au sein de la bibliothèque PaMPA de gestion parallèle de maillages distribués. Cette méthode est validée dans le cadre d'une simulation LES industrielle de chambre de combustion de turbine d'hélicoptère, portant sur un maillage à plus d'un milliard d'éléments

Parallel unstructured solvers for linear partial differential equations

This thesis presents the development of a parallel algorithm to solve symmetric systems of linear equations and the computational implementation of a parallel partial differential equations solver for unstructured meshes. The proposed method, called distributive conjugate gradient - DCG, is based on a single-level domain decomposition method and the conjugate gradient method to obtain a highly scalable parallel algorithm. An overview on methods for the discretization of domains and partial differential equations is given. The partition and refinement of meshes is discussed and the formulation of the weighted residual method for two- and three-dimensions presented. Some of the methods to solve systems of linear equations are introduced, highlighting the conjugate gradient method and domain decomposition methods. A parallel unstructured PDE solver is proposed and its actual implementation presented. Emphasis is given to the data partition adopted and the scheme used for communication among adjacent subdomains is explained. A series of experiments in processor scalability is also reported. The derivation and parallelization of DCG are presented and the method validated throughout numerical experiments. The method capabilities and limitations were investigated by the solution of the Poisson equation with various source terms. The experimental results obtained using the parallel solver developed as part of this work show that the algorithm presented is accurate and highly scalable, achieving roughly linear parallel speed-up in many of the cases tested

Parallel Tetrahedral Mesh Adaptation with Dynamic Load Balancing

The ability to dynamically adapt an unstructured grid is a powerful tool for efficiently solving computational problems with evolving physical features. In this paper, we report on our experience parallelizing an edge-based adaptation scheme, called 3D_TAG. using message passing. Results show excellent speedup when a realistic helicopter rotor mesh is randomly refined. However. performance deteriorates when the mesh is refined using a solution-based error indicator since mesh adaptation for practical problems occurs in a localized region., creating a severe load imbalance. To address this problem, we have developed PLUM, a global dynamic load balancing framework for adaptive numerical computations. Even though PLUM primarily balances processor workloads for the solution phase, it reduces the load imbalance problem within mesh adaptation by repartitioning the mesh after targeting edges for refinement but before the actual subdivision. This dramatically improves the performance of parallel 3D_TAG since refinement occurs in a more load balanced fashion. We also present optimal and heuristic algorithms that, when applied to the default mapping of a parallel repartitioner, significantly reduce the data redistribution overhead. Finally, portability is examined by comparing performance on three state-of-the-art parallel machines

Parallel unstructured solvers for linear partial differential equations

This thesis presents the development of a parallel algorithm to solve symmetric systems of linear equations and the computational implementation of a parallel partial differential equations solver for unstructured meshes. The proposed method, called distributive conjugate gradient - DCG, is based on a single-level domain decomposition method and the conjugate gradient method to obtain a highly scalable parallel algorithm. An overview on methods for the discretization of domains and partial differential equations is given. The partition and refinement of meshes is discussed and the formulation of the weighted residual method for two- and three-dimensions presented. Some of the methods to solve systems of linear equations are introduced, highlighting the conjugate gradient method and domain decomposition methods. A parallel unstructured PDE solver is proposed and its actual implementation presented. Emphasis is given to the data partition adopted and the scheme used for communication among adjacent subdomains is explained. A series of experiments in processor scalability is also reported. The derivation and parallelization of DCG are presented and the method validated throughout numerical experiments. The method capabilities and limitations were investigated by the solution of the Poisson equation with various source terms. The experimental results obtained using the parallel solver developed as part of this work show that the algorithm presented is accurate and highly scalable, achieving roughly linear parallel speed-up in many of the cases tested.EThOS - Electronic Theses Online ServiceGBUnited Kingdo