International audienceWe present new algorithms to detect and correct errors in the lower-upper factorization of a matrix, or the triangular linear system solution, over an arbitrary field. Our main algorithms do not require any additional information or encoding other than the original inputs and the erroneous output. Their running time is softly linear in the dimension times the number of errors when there are few errors, smoothly growing to the cost of fast matrix multiplication as the number of errors increases. We also present applications to general linear system solving
We consider the cost of estimating an error bound for the computed solution of a system of linear eq...
AbstractA new parallel algorithm for the LU factorization of a given dense matrix A is described. Th...
International audienceWe introduce a novel approach to exploit mixed precision arithmetic for low-ra...
International audienceWe present new algorithms to detect and correct errors in the lower-upper fact...
International audienceThe process of finding the solution of a linear system of equations is often t...
A new backward error analysis of LU factorization is presented. It allows do obtain a sharper up...
Abstract- This paper presents a new approach for the solution of Linear Programming Problems with th...
Abstract. Assuming standard floating-point arithmetic (in base β, precision p) and barring underflow...
We propose a reproducible variant of the unblocked LU factorization for graphics processor units (GP...
This paper presents an algorithm based fault tolerance method to harden three two-sided matrix facto...
Dense matrix factorizations like LU, Cholesky and QR are widely used for scientific applications tha...
We consider ill-conditioned linear systems $Ax =$ b that are to be solved iteratively, and assume t...
International audienceThis paper compares several fault-tolerance methods for the detection and corr...
AbstractThis paper gives a classification for the triangular factorization of square matrices. These...
The minimal 2-norm solution to an underdetermined system $Ax = b$ of full rank can be computed using...
We consider the cost of estimating an error bound for the computed solution of a system of linear eq...
AbstractA new parallel algorithm for the LU factorization of a given dense matrix A is described. Th...
International audienceWe introduce a novel approach to exploit mixed precision arithmetic for low-ra...
International audienceWe present new algorithms to detect and correct errors in the lower-upper fact...
International audienceThe process of finding the solution of a linear system of equations is often t...
A new backward error analysis of LU factorization is presented. It allows do obtain a sharper up...
Abstract- This paper presents a new approach for the solution of Linear Programming Problems with th...
Abstract. Assuming standard floating-point arithmetic (in base β, precision p) and barring underflow...
We propose a reproducible variant of the unblocked LU factorization for graphics processor units (GP...
This paper presents an algorithm based fault tolerance method to harden three two-sided matrix facto...
Dense matrix factorizations like LU, Cholesky and QR are widely used for scientific applications tha...
We consider ill-conditioned linear systems $Ax =$ b that are to be solved iteratively, and assume t...
International audienceThis paper compares several fault-tolerance methods for the detection and corr...
AbstractThis paper gives a classification for the triangular factorization of square matrices. These...
The minimal 2-norm solution to an underdetermined system $Ax = b$ of full rank can be computed using...
We consider the cost of estimating an error bound for the computed solution of a system of linear eq...
AbstractA new parallel algorithm for the LU factorization of a given dense matrix A is described. Th...
International audienceWe introduce a novel approach to exploit mixed precision arithmetic for low-ra...