This paper describes a new QR factorization algorithm which is especially designed for massively parallel platforms combining parallel distributed multi-core nodes. These platforms make the present ...

We consider computing the QR factorization with column pivoting (QRCP) for a tall and skinny matrix, which has important applications including low-rank approximation and rank determination. Motivated ...

QR-decomposition based QR-algorithm for eigenvalues evaluation of symmetric matrix with real values with OpenMP directives for parallelization of computations for multi-core systems ...

If the source matrix is a covariance matrix, then using Cholesky decomposition is efficient. The implementation of QR-Householder matrix inverse presented in this article emphasizes simplicity and ...

In this paper, by exploiting the special structure of the least squares problem and working on the problem directly, a numerically stable QR decomposition based algorithm is presented for the problem.

Parallel algorithms for singular value decomposition (SVD) have risen to prominence as an indispensable tool in high-performance numerical linear algebra. They offer significant improvements in ...