Parallel (M−N)SVD algorithms on the SIMD computers
Wang Guorong, Wei Yimin · Wuhan University Journal of Natural Sciences · 1996
Let A be m by n matrix, M and N be positive definite matrices of order m and n respectively. This paper presents an efficient method for computing ( M−N ) singular value decomposition (( M−N) SVD ) of A on a cube connected single instruction stream-multiple data stream (SIMD) parallel computer. This method is based on a one-sided orthogonalization algorithm due to Hestenes. On the cube connected SIMD parallel computer with o(n) processors, the ( M−N ) SVD of a matrix A requires a computation time of o ( m 3 log m/n ).