Developer Guide for Intel® Data Analytics Acceleration Library 2016 Update 4
QR decomposition is a matrix factorization technique that decomposes a matrix into a product of an orthogonal matrix Q and an upper triangular matrix R.
QR decomposition is used in solving linear inverse and least squares problems. It also serves as a basis for algorithms that find eigenvalues and eigenvectors.