We address synchronization issues of some block matrix multiplication algorithms in a distributed computing environment. We discuss performance behavior of a client/server implementation of these algorithms focusing on the most appropriate version which delivers the minimum synchronization overhead. Numerical experiments are carried out using the NetSolve distributed computing system. This work has been partially supported by Italian Ministry of Education, University and Research (MIUR) within the activities of the WP9 workpackage Grid Enabled Scientific Libraries, coordinated by A. Murli, part of the MIUR FIRB RBNE01KNFP Grid.it projec
This paper describes a novel parallel algorithm that implements a dense matrix multiplication operat...
Matrix multiplication is a fundamental building block in many machine learning models. As the input ...
Matrix multiplication is taken as a test bed for parallel processing on heterogeneous networks of wo...
We address synchronization issues of some block matrix multiplication algorithms in a distributed co...
Parallel computing on networks of workstations are intensively used in some application areas such a...
In this paper, an adaptive matrix multiplication algorithm for dynamic heterogeneous environments is...
In this paper we study the impact of the simultaneous exploitation of data- and task-parallelism, so...
The multiplication of a vector by a matrix is the kernel operation in many algorithms used in scient...
Matrix multiplication is one of the important operations in scientific and engineering application. ...
We present a new fast and scalable matrix multiplication algorithm, called DIMMA (Distribution-Indep...
Abstract. NetSolve is a kind of grid middleware used for high performance compute. In this article, ...
A parallel matrix multiplication algorithm is presented, and studies of its performance and estimati...
Parallel computing on networks of workstations are intensively used in some application areas such a...
AbstractÐIn this paper, we address the issue of implementing matrix multiplication on heterogeneous ...
Proceedings of the 8th IEEE International Conference on Cluster Computing (Cluster 2006), October, 2...
This paper describes a novel parallel algorithm that implements a dense matrix multiplication operat...
Matrix multiplication is a fundamental building block in many machine learning models. As the input ...
Matrix multiplication is taken as a test bed for parallel processing on heterogeneous networks of wo...
We address synchronization issues of some block matrix multiplication algorithms in a distributed co...
Parallel computing on networks of workstations are intensively used in some application areas such a...
In this paper, an adaptive matrix multiplication algorithm for dynamic heterogeneous environments is...
In this paper we study the impact of the simultaneous exploitation of data- and task-parallelism, so...
The multiplication of a vector by a matrix is the kernel operation in many algorithms used in scient...
Matrix multiplication is one of the important operations in scientific and engineering application. ...
We present a new fast and scalable matrix multiplication algorithm, called DIMMA (Distribution-Indep...
Abstract. NetSolve is a kind of grid middleware used for high performance compute. In this article, ...
A parallel matrix multiplication algorithm is presented, and studies of its performance and estimati...
Parallel computing on networks of workstations are intensively used in some application areas such a...
AbstractÐIn this paper, we address the issue of implementing matrix multiplication on heterogeneous ...
Proceedings of the 8th IEEE International Conference on Cluster Computing (Cluster 2006), October, 2...
This paper describes a novel parallel algorithm that implements a dense matrix multiplication operat...
Matrix multiplication is a fundamental building block in many machine learning models. As the input ...
Matrix multiplication is taken as a test bed for parallel processing on heterogeneous networks of wo...