The traditional wisdom concerning GMRES(m) is that the larger the restart size 'm', the closer GMRES(m) mimics the convergence behavior of standard GMRES. It has been shown, however, that a smaller restart size can actually benefit certain small test problems. A modification called GMRES(P) replaces a single fixed restart size 'm' with a restart pattern 'P' where the restart size varies after each restart. GMRES(P) allows for the examination of this paradoxical behavior on a more general set of matrices. We observe that decreasing the Krylov subspace size for select restarts can reduce iteration counts. This talk will cover ongoing work on this phenomenon.