We propose a CORDIC-based Jacobi-like method for parallel computation of the eigenvalues of Hermitian (and real symmetric) matrices and the SVD of real matrices using inexact diagonalizations. It is predicted on the fact that exact diagonalization is not necessary for convergence and the potential increase in computation time due to concomitant linear convergence may be offset by reducing the time to evaluate and appply the inexact diagonalizations. We also present results of experiments on the CM5 to determine convergence behavior.