AbstractWe have recently multiprocessed a code for the direct solution of sparse linear equations on the Alliant FX/8. We discuss several issues which are involved, all of which are of relevance to any shared memory multiprocessor. Among these issues are the dynamic allocation of data, the management of task queues, task spawning, and the effect of controlling the granularity. We also show runs of our code under the SCHEDULE package from Argonne which presents a portable interface to users of parallel machines, allows the user to define the computational graph, and has very useful graphic output to a SUN workstation. Our tailored code attains a speedup by a factor of about six on the eight processors of the Alliant. We suggest ways of impro...
Vector computers have been extensively used for years in matrix algebra to treat with large dense ma...
International audienceIn this paper, we propose a generic method of automatic parallelization for sp...
This dissertation presents an architecture to accelerate sparse matrix linear algebra,which is among...
AbstractWe have recently multiprocessed a code for the direct solution of sparse linear equations on...
Gary Kumfert and Alex Pothen have improved the quality and run time of two ordering algorithms for m...
International audienceTo face the advent of multicore processors and the ever increasing complexity ...
Direct methods for the solution of sparse systems of linear equations are used in a wide range of nu...
We consider the solution of very large sparse systems of linear equations on parallel architectures....
Nous nous intéressons à la résolution de systèmes linéaires creux de très grande taille par des méth...
Scientific workloads are often described as directed acyclic task graphs. In this paper, we focus o...
La résolution de grands systèmes linéaires creux est un élément essentiel des simulations numériques...
Sparse linear systems occur in areas such as finite element methods and statistics. These system...
Problems in the class of unstructured sparse matrix computations are characterized by highly irregul...
This paper provides a comprehensive study and comparison of two state-of-the-art direct solvers for ...
We consider the solution of very large systems of linear equations with direct multifrontal methods....
Vector computers have been extensively used for years in matrix algebra to treat with large dense ma...
International audienceIn this paper, we propose a generic method of automatic parallelization for sp...
This dissertation presents an architecture to accelerate sparse matrix linear algebra,which is among...
AbstractWe have recently multiprocessed a code for the direct solution of sparse linear equations on...
Gary Kumfert and Alex Pothen have improved the quality and run time of two ordering algorithms for m...
International audienceTo face the advent of multicore processors and the ever increasing complexity ...
Direct methods for the solution of sparse systems of linear equations are used in a wide range of nu...
We consider the solution of very large sparse systems of linear equations on parallel architectures....
Nous nous intéressons à la résolution de systèmes linéaires creux de très grande taille par des méth...
Scientific workloads are often described as directed acyclic task graphs. In this paper, we focus o...
La résolution de grands systèmes linéaires creux est un élément essentiel des simulations numériques...
Sparse linear systems occur in areas such as finite element methods and statistics. These system...
Problems in the class of unstructured sparse matrix computations are characterized by highly irregul...
This paper provides a comprehensive study and comparison of two state-of-the-art direct solvers for ...
We consider the solution of very large systems of linear equations with direct multifrontal methods....
Vector computers have been extensively used for years in matrix algebra to treat with large dense ma...
International audienceIn this paper, we propose a generic method of automatic parallelization for sp...
This dissertation presents an architecture to accelerate sparse matrix linear algebra,which is among...