Sparse linear systems occur in areas such as finite element methods and statistics. These systems are often solved on parallel computers due to their size. In this paper a theoretical analysis of parallel sparse QR factorisation using a multifrontal method is undertaken. The analysis is quantified by some estimates of parallel speeds up for various parallel computers. These estimates show that only moderate parallel speedups can be attained
We present a simulation-based performance model to analyze a parallel sparse LU factorization algori...
We present a performance model to analyze a parallel sparse LU factorization algorithm on modern ca...
For many finite element problems, when represented as sparse matrices, iterative solvers are found t...
Sparse linear systems occur in areas such as finite element methods and statistics. These system...
SuiteSparseQR is a sparse multifrontal QR factorization algorithm. Dense matrix methods within each ...
International audienceThe advent of multicore processors represents a disruptive event in the histor...
We present a performance model to analyze a parallel sparseLU factorization algorithm on modern cach...
We describe the issues involved in the design and implementation of efficient parallel algorithms fo...
AbstractThis paper discusses an extension of the pipelined Givens method for computing the QR factor...
This article addresses the problems of memory man-agement in a parallel sparse matrix factorization ...
We present a parallel algorithm for the QR factorization with column pivoting of a sparse matrix by ...
International audienceTo face the advent of multicore processors and the ever increasing complexity ...
Nous nous intéressons à la résolution de systèmes linéaires creux de très grande taille par des méth...
To face the advent of multicore processors and the ever increasing complexity of hardware architectu...
A few parallel algorithms for solving triangular systems resulting from parallel factorization of sp...
We present a simulation-based performance model to analyze a parallel sparse LU factorization algori...
We present a performance model to analyze a parallel sparse LU factorization algorithm on modern ca...
For many finite element problems, when represented as sparse matrices, iterative solvers are found t...
Sparse linear systems occur in areas such as finite element methods and statistics. These system...
SuiteSparseQR is a sparse multifrontal QR factorization algorithm. Dense matrix methods within each ...
International audienceThe advent of multicore processors represents a disruptive event in the histor...
We present a performance model to analyze a parallel sparseLU factorization algorithm on modern cach...
We describe the issues involved in the design and implementation of efficient parallel algorithms fo...
AbstractThis paper discusses an extension of the pipelined Givens method for computing the QR factor...
This article addresses the problems of memory man-agement in a parallel sparse matrix factorization ...
We present a parallel algorithm for the QR factorization with column pivoting of a sparse matrix by ...
International audienceTo face the advent of multicore processors and the ever increasing complexity ...
Nous nous intéressons à la résolution de systèmes linéaires creux de très grande taille par des méth...
To face the advent of multicore processors and the ever increasing complexity of hardware architectu...
A few parallel algorithms for solving triangular systems resulting from parallel factorization of sp...
We present a simulation-based performance model to analyze a parallel sparse LU factorization algori...
We present a performance model to analyze a parallel sparse LU factorization algorithm on modern ca...
For many finite element problems, when represented as sparse matrices, iterative solvers are found t...