Parallel algorithms for QR decomposition on a shared memory multiprocessor

Various parallel implementations of algorithms for the QR decomposition of a matrix are compared using shared memory multiprocessors. Algorithms based on both Givens and Householder transformations are considered. A number of parallelisation techniques are used with particular emphasis on algorithms which allocate work to tasks dynamically. The results indicate that one version is significantly better than the others.