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A class of communication-avoiding algorithms for solving general dense linear...
We study several solvers for the solution of general linear systems where the main objective is to reduce the communication overhead due to pivoting. We first describe... -
Introduction of shared-memory parallelism in a distributed-memory multifronta...
We study the adaptation of a parallel distributed-memory solver towards a shared-memory code, targeting multi-core architectures. The advantage of adapting the code... -
Calculs pour les matrices denses : coût de communication et stabilité numérique
This dissertation focuses on a widely used linear algebra kernel to solve linear systems, that is the LU decomposition. Usually, to perform such a computation one uses... -
Nonnegative Joint Diagonalization by Congruence Based on LU Matrix Factorization
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LU Factorization with Panel Rank Revealing Pivoting and its Communication Avo...
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Contribution to the mathematical analysis and to the numerical solution of an...
The determination of the shape of an elastic obstacle immersed in water from some measurements of the scattered field is an important problem in many technologies such... -
Accelerating linear system solutions using randomization technique
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Jacobi-like nonnegative joint diagonalization by congruence
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Using Random Butterfly Transformations to Avoid Pivoting in Sparse Direct Met...
Also appeared as Lapack Working Note 285 -
Locality optimization on a NUMA architecture for hybrid LU factorization
We study the impact of non-uniform memory accesses (NUMA) on the solution of dense general linear systems using an LU factorization algorithm. In particular we... -
Improved backward error bounds for LU and Cholesky factorizations
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Locality Optimization on a NUMA Architecture for Hybrid LU Factorization
International audience
