  The simulation of lattice QCD on massively parallel computers stimulated the
development of scalable algorithms for the solution of sparse linear systems.
We tackle the problem of the Wilson-Dirac operator inversion by combining a
Schwarz alternating procedure (SAP) in multiplicative form with a flexible
variant of the GMRES-DR algorithm. We show that restarted GMRES is not able to
converge when the system is poorly conditioned. By adding deflation in the form
of the FGMRES-DR algorithm, an important fraction of the information produced
by the iterates is kept between successive restarts leading to convergence in
cases in which FGMRES stagnates.
