Preconditioned HSS methods for the solution of non-Hermitian positive definite linear systems and applications to the discrete convection-diffusion equation

Summary. We study the role of preconditioning strategies recently developed for coercive problems in connection with a two-step iterative method, based on the Hermitian skew-Hermitian splitting (HSS) of the coefficient matrix, proposed by Bai, Golub and Ng for the solution of nonsymmetric linear systems whose real part is coercive. As a model problem we consider Finite Differences (FD) matrix sequences {A_n(a,p)}_n discretizing the elliptic (convection-diffusion) problem with being a plurirectangle of R^d with a(x) being a uniformly positive function and p(x) denoting the Reynolds function: here for plurirectangle we mean a connected union of rectangles in d dimensions with edges parallel to the axes. More precisely, in connection with preconditioned HSS/GMRES like methods, we consider the preconditioning sequence {P_n(a)}_n, P_n(a):= D_n^1/2(a)A_n(1,0) D_n^1/2(a) where D_n(a) is the suitably scaled main diagonal of A_n(a,0). If a(x) is positive and regular enough, then the preconditioned sequence shows a strong clustering at unity so that the sequence {P_n(a)}_n turns out to be a superlinear preconditioning sequence for {A_n(a,0)}_n where A_n(a,0) represents a good approximation of Re(A_n(a,p)) namely the real part of A_n(a,p). The computational interest is due to the fact that the preconditioned HSS method has a convergence behavior depending on the spectral properties of {P_n^-1(a)Re(A_n(a,p))}_n {P_n^-1(a)A_n(a,0)}_n: therefore the solution of a linear system with coefficient matrix A_n(a,p) is reduced to computations involving diagonals and to the use of fast Poisson solvers for {A_n(1,0)}_n.Some numerical experimentations confirm the optimality of the discussed proposal and its superiority with respect to existing techniques.Mathematics Subject Classification (1991): 65F10, 65N22, 15A18, 15A12, 47B65