In this paper we describe a general adaptive finite element framework for unstructured tetrahedral meshes without hanging nodes suitable for large scale parallel computations. Our framework is designed to scale linearly to several thousands of processors, using fully distributed and efficient algorithms. The key components of our implementation, local mesh refinement and load balancing algorithms, are described in detail. Finally, we present a theoretical and experimental performance study of our framework, used in a large scale computational fluid dynamics computation, and we compare scaling and complexity of different algorithms on different massively parallel architectures.QC 20120326</p
The efficient solution of many large-scale scientific calculations depends on unstructured mesh stra...
The present article describes a simple element-driven strategy for the conforming refinement of simp...
Abstract. Load balancing plays an important role in parallel numer-ical simulations. State-of-the-ar...
In this paper we describe a general adaptive finite element framework for unstructured tetrahedral m...
Today’s largest supercomputers have 100,000s of processor cores and offer the potential to solve par...
this paper we have introduced a parallelization for the calculation of fluid flow problems on unstru...
This paper provides an overview of data structures suitable for distributed storage of finite elemen...
We present a new approach to the use of parallel computers with adaptive finite element methods. Thi...
Computational methods based on the use of adaptively constructed nonuniform meshes reduce the amount...
The majority of finite element models in structural engineering are composed of unstructured meshes....
. An explicit finite element scheme based on a two step Taylor-Galerkin algorithm allows the solutio...
In parallel adaptive finite element simulations the work load on the individual processors may chang...
Abstract. In this paper, we give an overview of efforts to improve current techniques of load-balanc...
The present article describes a simple element-driven strategy for the conforming refinement of simp...
The $hp$-adaptive finite element method (FEM) - where one independently chooses the mesh size ($h$) ...
The efficient solution of many large-scale scientific calculations depends on unstructured mesh stra...
The present article describes a simple element-driven strategy for the conforming refinement of simp...
Abstract. Load balancing plays an important role in parallel numer-ical simulations. State-of-the-ar...
In this paper we describe a general adaptive finite element framework for unstructured tetrahedral m...
Today’s largest supercomputers have 100,000s of processor cores and offer the potential to solve par...
this paper we have introduced a parallelization for the calculation of fluid flow problems on unstru...
This paper provides an overview of data structures suitable for distributed storage of finite elemen...
We present a new approach to the use of parallel computers with adaptive finite element methods. Thi...
Computational methods based on the use of adaptively constructed nonuniform meshes reduce the amount...
The majority of finite element models in structural engineering are composed of unstructured meshes....
. An explicit finite element scheme based on a two step Taylor-Galerkin algorithm allows the solutio...
In parallel adaptive finite element simulations the work load on the individual processors may chang...
Abstract. In this paper, we give an overview of efforts to improve current techniques of load-balanc...
The present article describes a simple element-driven strategy for the conforming refinement of simp...
The $hp$-adaptive finite element method (FEM) - where one independently chooses the mesh size ($h$) ...
The efficient solution of many large-scale scientific calculations depends on unstructured mesh stra...
The present article describes a simple element-driven strategy for the conforming refinement of simp...
Abstract. Load balancing plays an important role in parallel numer-ical simulations. State-of-the-ar...