Parallelization of SVD of a matrix-systolic approach

In this paper we investigate the parallelization of Hestenes-Jacobi method for computing the SVD of an MXN matrix using systolic arrays. In the case of real matrix an array of R² processors is proposed, such that each row contains N columns. In order to extend this idea we have presented three transformations which are used for transforming the complex into the real matrix. After the additional computations, we show how the same array may be used for the SVD of a complex matrix.