A parallel algorithm for finding the inverse of the matrix using Gauss Jordan method in OpenMP. The Gauss Jordan method has been chosen for this project because it provides a direct method for obtaining inverse matrix and requires approx. 50 % fewer operations unlike other methods. Hence forth it is suitable for massive parallelization. Then, authors have analyzed the parallel algorithm for computing the inverse of the matrix and compared it with its perspective sequential algorithm in terms of run time, speed-up and efficiency. Further, the obtained result is used to propose a new method of Message Sharing (called Coding Theory). The proposed method is simple and has a great potential to be applied to other situation where the exchange of ...
2nonenoneMARTINEZ CALOMARDO ANGELES; Mas JoséMARTINEZ CALOMARDO, Angeles; Mas, Jos
A parallel computation model to invert a lower triangular matrix using Gauss elimination with sweepi...
We consider the parallel computation of the diagonal of the inverse of a large sparse matrix. This p...
Abstract:- A matrix inversion algorithm based on the Sherman-Morrison formula is analyzed and compar...
The performance of a parallel Gauss-Jordan matrix inversion algorithm on the Mark II hypercube3 at C...
We study the use of massively parallel architectures for computing a matrix inverse. Two different ...
Parallel Gaussian elimination technique for the solution of a system of equations Ax C where A is a ...
This paper presents a parallel adaptive version of the block-based Gauss-Jordan algorithm used in nu...
The model of bulk-synchronous parallel (BSP) computation is an emerging paradigm of general-purpose ...
We study parallelization of direct methods on shared and distributed memory computers using OpenMP a...
English: In this project several mathematic algorithms are developed to obtain a matrix inversion me...
This paper provides an introduction to algorithms for fundamental linear algebra problems on various...
An extremely common bottleneck encountered in statistical learning algorithms is inversion of huge c...
The main goal of this research is to use OpenMP, Posix Threads and Microsoft Parallel Patterns libra...
The mirin contribution of this report is the development of novel algorithms {that make efficient us...
2nonenoneMARTINEZ CALOMARDO ANGELES; Mas JoséMARTINEZ CALOMARDO, Angeles; Mas, Jos
A parallel computation model to invert a lower triangular matrix using Gauss elimination with sweepi...
We consider the parallel computation of the diagonal of the inverse of a large sparse matrix. This p...
Abstract:- A matrix inversion algorithm based on the Sherman-Morrison formula is analyzed and compar...
The performance of a parallel Gauss-Jordan matrix inversion algorithm on the Mark II hypercube3 at C...
We study the use of massively parallel architectures for computing a matrix inverse. Two different ...
Parallel Gaussian elimination technique for the solution of a system of equations Ax C where A is a ...
This paper presents a parallel adaptive version of the block-based Gauss-Jordan algorithm used in nu...
The model of bulk-synchronous parallel (BSP) computation is an emerging paradigm of general-purpose ...
We study parallelization of direct methods on shared and distributed memory computers using OpenMP a...
English: In this project several mathematic algorithms are developed to obtain a matrix inversion me...
This paper provides an introduction to algorithms for fundamental linear algebra problems on various...
An extremely common bottleneck encountered in statistical learning algorithms is inversion of huge c...
The main goal of this research is to use OpenMP, Posix Threads and Microsoft Parallel Patterns libra...
The mirin contribution of this report is the development of novel algorithms {that make efficient us...
2nonenoneMARTINEZ CALOMARDO ANGELES; Mas JoséMARTINEZ CALOMARDO, Angeles; Mas, Jos
A parallel computation model to invert a lower triangular matrix using Gauss elimination with sweepi...
We consider the parallel computation of the diagonal of the inverse of a large sparse matrix. This p...