Editing QR decomposition (section)

====Parallel implementation of Householder QR====

The Householder QR method can be implemented in parallel with algorithms such as the TSQR algorithm (which stands for ''Tall Skinny QR''). This algorithm can be applied in the case when the matrix ''A'' has ''m >> n''.<ref>Communication-optimal parallel and sequential QR and LU factorizations: theory and practice, James Demmel and Laura Grigori, 2008,
https://arxiv.org/abs/0806.2159, 
</ref> This algorithm uses a binary reduction tree to compute local householder QR decomposition at each node in the forward pass, and re-constitute the Q matrix in the backward pass. The [[binary tree]] structure aims at decreasing the amount of communication between processor to increase performance.