In parallel finite element solvers, sparse matrix assembly is often a bottleneck. Implemented using message passing, latency from message matching starts to limit performance as the number of cores increases. We here address this issue by using our own stack based representation of the sparse matrix, and a hybrid parallel programming model combining traditional message passing with one-sided communication. This gives an significantly faster insertion rate compared to state of the art implementations on a Cray XE6.QC 20130815</p
For many finite element problems, when represented as sparse matrices, iterative solvers are found t...
Parallel sparse matrix-matrix multiplication algorithms (PSpGEMM) spend most of their running time o...
We present a static parallel implementation of themultifrontal method to solve unsymmetric sparse li...
AbstractWe discuss some aspects of implementing the finite-element method on parallel computers with...
Sparse matrix operations dominate the cost of many scientific applications. In parallel, the perform...
Key words: finite element method, multifrontal solver, load balancing We work on direct methods to s...
The finite element method (FEM) is one of the most commonly used techniques for the solution of part...
The assembly of sparse matrices is a key operation in finite element methods. In this study we analy...
The finite element method (FEM) is one of the most commonly used techniques for the solution of part...
We present our work on developing a hybrid parallel programming model for a general finite element s...
We present our work on developing a hybrid parallel programming model for a general finite element s...
Efficient data motion is critical for high performance computing on distributed memory architectures...
Abstract. Traditionally, numerical simulations based on finite element methods consider the algorith...
International audienceThere are three common parallel sparse matrix-vector multiply algorithms: 1D 3...
In this thesis, methods for efficient utilization of modern computer hardware for numerical simulati...
For many finite element problems, when represented as sparse matrices, iterative solvers are found t...
Parallel sparse matrix-matrix multiplication algorithms (PSpGEMM) spend most of their running time o...
We present a static parallel implementation of themultifrontal method to solve unsymmetric sparse li...
AbstractWe discuss some aspects of implementing the finite-element method on parallel computers with...
Sparse matrix operations dominate the cost of many scientific applications. In parallel, the perform...
Key words: finite element method, multifrontal solver, load balancing We work on direct methods to s...
The finite element method (FEM) is one of the most commonly used techniques for the solution of part...
The assembly of sparse matrices is a key operation in finite element methods. In this study we analy...
The finite element method (FEM) is one of the most commonly used techniques for the solution of part...
We present our work on developing a hybrid parallel programming model for a general finite element s...
We present our work on developing a hybrid parallel programming model for a general finite element s...
Efficient data motion is critical for high performance computing on distributed memory architectures...
Abstract. Traditionally, numerical simulations based on finite element methods consider the algorith...
International audienceThere are three common parallel sparse matrix-vector multiply algorithms: 1D 3...
In this thesis, methods for efficient utilization of modern computer hardware for numerical simulati...
For many finite element problems, when represented as sparse matrices, iterative solvers are found t...
Parallel sparse matrix-matrix multiplication algorithms (PSpGEMM) spend most of their running time o...
We present a static parallel implementation of themultifrontal method to solve unsymmetric sparse li...