The performance of a parallel Gauss-Jordan matrix inversion algorithm on the Mark II hypercube3 at Caltech is discussed. We will show that parallel Gauss-Jordan inversion is superior to parallel Gaussian elimination for inversion, and discuss the reasons for this. Empirical and theoretical efficiencies for parallel Gauss-Jordan inversion as a function of matrix dimension for different numbers and configurations of processors are presented. The theoretical efficiencies are in quantitative agreement with the empirical efficiencies
We analyze the performance-power-energy balance of a conventional Intel Xeon mul-ticore processor an...
This paper presents a parallel adaptive version of the block-based Gauss-Jordan algorithm used in nu...
The inversion of matrices was calculated on a single transputer and on a network of transputers to s...
The performance of a parallel Gauss-Jordan matrix inversion algorithm on the Mark II hypercube3 at C...
A parallel computation model to invert a lower triangular matrix using Gauss elimination with sweepi...
Abstract:- A matrix inversion algorithm based on the Sherman-Morrison formula is analyzed and compar...
Matrix inversion is a mathematical algorithm that is widely used and applied in many real time engin...
We study the use of massively parallel architectures for computing a matrix inverse. Two different ...
The mirin contribution of this report is the development of novel algorithms {that make efficient us...
As computing machines advance, new fields are explored and old ones are expanded. This thesis consid...
An extremely common bottleneck encountered in statistical learning algorithms is inversion of huge c...
[[abstract]]In this paper we use hypercube computers for solving linear systems. First, the pivoting...
English: In this project several mathematic algorithms are developed to obtain a matrix inversion me...
A parallel algorithm for finding the inverse of the matrix using Gauss Jordan method in OpenMP. The ...
We take advantage of the new tasking features in OpenMP to propose advanced task-parallel algorithms...
We analyze the performance-power-energy balance of a conventional Intel Xeon mul-ticore processor an...
This paper presents a parallel adaptive version of the block-based Gauss-Jordan algorithm used in nu...
The inversion of matrices was calculated on a single transputer and on a network of transputers to s...
The performance of a parallel Gauss-Jordan matrix inversion algorithm on the Mark II hypercube3 at C...
A parallel computation model to invert a lower triangular matrix using Gauss elimination with sweepi...
Abstract:- A matrix inversion algorithm based on the Sherman-Morrison formula is analyzed and compar...
Matrix inversion is a mathematical algorithm that is widely used and applied in many real time engin...
We study the use of massively parallel architectures for computing a matrix inverse. Two different ...
The mirin contribution of this report is the development of novel algorithms {that make efficient us...
As computing machines advance, new fields are explored and old ones are expanded. This thesis consid...
An extremely common bottleneck encountered in statistical learning algorithms is inversion of huge c...
[[abstract]]In this paper we use hypercube computers for solving linear systems. First, the pivoting...
English: In this project several mathematic algorithms are developed to obtain a matrix inversion me...
A parallel algorithm for finding the inverse of the matrix using Gauss Jordan method in OpenMP. The ...
We take advantage of the new tasking features in OpenMP to propose advanced task-parallel algorithms...
We analyze the performance-power-energy balance of a conventional Intel Xeon mul-ticore processor an...
This paper presents a parallel adaptive version of the block-based Gauss-Jordan algorithm used in nu...
The inversion of matrices was calculated on a single transputer and on a network of transputers to s...