A One-Sided Jacobi Algorithm for Computing the Singular Value Decomposition on a Vector Computer

An old algorithm for computing the singular value decomposition, which was first mentioned by Hestenes [SIAM J. Appl. Math., 6 (1958), pp. 51–90], has gained renewed interest because of its properties of parallelism and vectorizability. Some computational modifications are given and a comparison with the well-known Golub–Reinsch algorithm is made. Comparative experiments on a CYBER 205 are reported.