International audienceWe present a fast hybrid solver for dense linear systems based on LU factorization. To achieve good performance, we avoid pivoting by using random butterfly transformations for which we developed efficient implementations on heterogeneous architectures. We used both Graphics Processing Units and Intel Xeon Phi as accelerators. The performance results show that the pre-processing due to randomization is negligible and that the solver outperforms the corresponding routines based on partial pivoting
Sparse solver has become the bottleneck of SPICE simulators. There has been few work on GPU-based sp...
Abstract. We address some key issues in designing dense linear alge-bra (DLA) algorithms that are co...
We consider a fast, robust and scalable solver using graphic processing units (GPU) as accelerators ...
International audienceWe present a fast hybrid solver for dense linear systems based on LU factoriza...
International audienceWe illustrate how linear algebra calculations can be enhanced by statistical t...
In this PhD thesis, we study algorithms and implementations to accelerate the solution of dense line...
We illustrate how linear algebra calculations can be enhanced by statistical techniques in the case ...
AbstractWe study several solvers for the solution of general linear systems where the main objective...
We study several solvers for the solution of general linear systems where the main objective is to r...
Parallelizing the LU factorization of sparse Jacobian matrices reduces the execution time of the pow...
International audienceThis paper studies the performance of different algorithms for solving a dense...
Abstract—LU factorization with partial pivoting is a canonical numerical procedure and the main comp...
Lower-upper (LU) factorization is widely used in many scientific computations. It is one of the most...
AbstractLU factorization is the most computationally intensive step in solving systems of linear equ...
International audienceThis paper introduces hybrid LU-QR al- gorithms for solving dense linear syste...
Sparse solver has become the bottleneck of SPICE simulators. There has been few work on GPU-based sp...
Abstract. We address some key issues in designing dense linear alge-bra (DLA) algorithms that are co...
We consider a fast, robust and scalable solver using graphic processing units (GPU) as accelerators ...
International audienceWe present a fast hybrid solver for dense linear systems based on LU factoriza...
International audienceWe illustrate how linear algebra calculations can be enhanced by statistical t...
In this PhD thesis, we study algorithms and implementations to accelerate the solution of dense line...
We illustrate how linear algebra calculations can be enhanced by statistical techniques in the case ...
AbstractWe study several solvers for the solution of general linear systems where the main objective...
We study several solvers for the solution of general linear systems where the main objective is to r...
Parallelizing the LU factorization of sparse Jacobian matrices reduces the execution time of the pow...
International audienceThis paper studies the performance of different algorithms for solving a dense...
Abstract—LU factorization with partial pivoting is a canonical numerical procedure and the main comp...
Lower-upper (LU) factorization is widely used in many scientific computations. It is one of the most...
AbstractLU factorization is the most computationally intensive step in solving systems of linear equ...
International audienceThis paper introduces hybrid LU-QR al- gorithms for solving dense linear syste...
Sparse solver has become the bottleneck of SPICE simulators. There has been few work on GPU-based sp...
Abstract. We address some key issues in designing dense linear alge-bra (DLA) algorithms that are co...
We consider a fast, robust and scalable solver using graphic processing units (GPU) as accelerators ...