Add to ORKGAbstract. Based on Gaussian Belief Propagation(GaBP) algorithm for solving sparse symmetric linear equations, an iterative acceleration optimization method of GaBP is studied and a corre-sponding optimized storage scheme is proposed. We explore the parallelism and load balancing features of this algorithm and present a multicore-based parallel GaBP algorithm with dynam-ic load-balance. The numerical results indicate that this algorithm can solve large scale sparse symmetric linear equations with good results and high parallel efficiency
International audienceThe Gauss-Seidel method is very efficient for solving problems such as tightly...
Ponència presentada al Euro-Par 2016: Parallel Processing Workshops pp 121–133.The solution of spars...
We propose several techniques as alternatives to partial pivoting to stabilize sparse Gaussian elimi...
We present an implementation-oriented algorithm for the recently developed Gaussian Belief Propagati...
Solving Linear Equation System (LESs) is a common problem in numerous fields of science. Even though...
The computational efficiency of Finite Element Methods (FEMs) on parallel architectures is severely ...
In this paper, we present the main algorithmic features in the software package SuperLU_DIST, a dis...
In this paper, we present the main algorithmic features in the software package SuperLU{_}DIST, a di...
With the introduction of programmable graphical processing units (GPU) in the last decade, Heterogen...
Abstract — The canonical problem of solving a system of linear equations arises in numerous contexts...
With the increase of size and complexity of interconnected power system, the dynamic stability simul...
With the increase of size and complexity of interconnected power system, the dynamic stability simul...
An extremely common bottleneck encountered in statistical learning algorithms is inversion of huge c...
This study presents a new parallel Gaussian elimination approach for symmetric positive definite ban...
We consider several issues involved in the solution of sparse symmetric positive definite system b...
International audienceThe Gauss-Seidel method is very efficient for solving problems such as tightly...
Ponència presentada al Euro-Par 2016: Parallel Processing Workshops pp 121–133.The solution of spars...
We propose several techniques as alternatives to partial pivoting to stabilize sparse Gaussian elimi...
We present an implementation-oriented algorithm for the recently developed Gaussian Belief Propagati...
Solving Linear Equation System (LESs) is a common problem in numerous fields of science. Even though...
The computational efficiency of Finite Element Methods (FEMs) on parallel architectures is severely ...
In this paper, we present the main algorithmic features in the software package SuperLU_DIST, a dis...
In this paper, we present the main algorithmic features in the software package SuperLU{_}DIST, a di...
With the introduction of programmable graphical processing units (GPU) in the last decade, Heterogen...
Abstract — The canonical problem of solving a system of linear equations arises in numerous contexts...
With the increase of size and complexity of interconnected power system, the dynamic stability simul...
With the increase of size and complexity of interconnected power system, the dynamic stability simul...
An extremely common bottleneck encountered in statistical learning algorithms is inversion of huge c...
This study presents a new parallel Gaussian elimination approach for symmetric positive definite ban...
We consider several issues involved in the solution of sparse symmetric positive definite system b...
International audienceThe Gauss-Seidel method is very efficient for solving problems such as tightly...
Ponència presentada al Euro-Par 2016: Parallel Processing Workshops pp 121–133.The solution of spars...
We propose several techniques as alternatives to partial pivoting to stabilize sparse Gaussian elimi...