In this work we present a parallel algorithm for the so-lution of a least squares problem with structured matri-ces. This problem arises in many applications mainly re-lated to digital signal processing. The parallel algorithm is designed to speed up the sequential one on heteroge-neous networks of computers. The parallel algorithm fol-lows the HeHo strategy (Heterogeneous distribution of pro-cesses over processors with homogeneous distribution of computations over the processes) and is implemented us-ing HeteroMPI, a recently developed extension of MPI for programming high performance computations on heteroge-neous networks of computers. The obtained results validate HeteroMPI as a very useful tool for portable implementa-tion of parallel ...
International audienceFuture computing platforms will be distributed and heterogeneous. Such platfor...
Abstract. The paper presents a new data partitioning algorithm for parallel computing on heterogeneo...
Abstract Efficiently solving large sparse linear systems on loosely coupled net-works of computers i...
In this work we present two parallel algorithms for the solution of a given least squares problem wi...
In this work we present two parallel algorithms for the solution of a given least squares problem wi...
In this paper we study the parallelization of PCGLS, a basic iterative method whose main idea is to ...
This paper presents and analyzes two different strategies of heterogeneous distribution of computati...
. In this paper we mainly focus on the study of the parallelization of PCGLS, a basic iterative meth...
In this paper the parallelization of a new learning algorithm for multilayer perceptrons, specifical...
Due to the character of the original source materials and the nature of batch digitization, quality ...
In this paper we study the parallel aspects of PCGLS, a basic iterative method whose main idea is to...
Least squares solutions are a very important problem, which appear in a broad range of disciplines (...
Abstract. The paper presents a tool that ports ScaLAPACK programs designed to run on massively paral...
This paper presents a self-optimization methodology for parallel linear algebra rou-tines on heterog...
Future computing platforms will be distributed and heterogeneous. Such platforms range from heteroge...
International audienceFuture computing platforms will be distributed and heterogeneous. Such platfor...
Abstract. The paper presents a new data partitioning algorithm for parallel computing on heterogeneo...
Abstract Efficiently solving large sparse linear systems on loosely coupled net-works of computers i...
In this work we present two parallel algorithms for the solution of a given least squares problem wi...
In this work we present two parallel algorithms for the solution of a given least squares problem wi...
In this paper we study the parallelization of PCGLS, a basic iterative method whose main idea is to ...
This paper presents and analyzes two different strategies of heterogeneous distribution of computati...
. In this paper we mainly focus on the study of the parallelization of PCGLS, a basic iterative meth...
In this paper the parallelization of a new learning algorithm for multilayer perceptrons, specifical...
Due to the character of the original source materials and the nature of batch digitization, quality ...
In this paper we study the parallel aspects of PCGLS, a basic iterative method whose main idea is to...
Least squares solutions are a very important problem, which appear in a broad range of disciplines (...
Abstract. The paper presents a tool that ports ScaLAPACK programs designed to run on massively paral...
This paper presents a self-optimization methodology for parallel linear algebra rou-tines on heterog...
Future computing platforms will be distributed and heterogeneous. Such platforms range from heteroge...
International audienceFuture computing platforms will be distributed and heterogeneous. Such platfor...
Abstract. The paper presents a new data partitioning algorithm for parallel computing on heterogeneo...
Abstract Efficiently solving large sparse linear systems on loosely coupled net-works of computers i...