Neumann Series in MGS-GMRES and Inner-Outer Iterations: Preprint

Stephen Thomas, Katarzyna Swirydowicz, Ruipeng Li, Paul Mullowney

Research output: Contribution to conferencePaper

Abstract

A low-synchronization MGS-GMRES Krylov solver employing a truncated Neumann series for the inverse compact WY MGS correction matrix T is presented. A corollary to the backward stability result of Paige et al. [1] establishes that T = I - Lk is sufficient for convergence of GMRES when kLkp F = O("p)_p F (B), where the strictly lower triangular matrix L is defined by the inner products of Krylov vectors V T 1:k-2 vk-1. The preconditioner is the classical Ruge-Stuben AMG algorithm with compatible relaxation and inner-outer Gauss-Seidel smoother. This smoother may also be expressed as a truncated Neumann series. Drop tolerances are applied to the lower triangular matrices arising in the smoother in order to reduce the number of non-zeros and accelerate the time to solution. The number of small matrix elements are found to increase from fine to coarse levels and thus the effciency gains are greater for large problems with many levels in the V -cycle. The solver is applied to the pressure continuity equation for the incompressible Navier-Stokes equations. Unlike the inner-outer iteration, the solver convergence rate with the standard Gauss-Seidel smoother deteriorates with dropping. The solver compute time is reduced by up to 50% without a change in the convergence rate.
Original languageAmerican English
Number of pages23
StatePublished - 2022
EventSISC Copper Mountain Special Section -
Duration: 25 Mar 202131 Mar 2021

Conference

ConferenceSISC Copper Mountain Special Section
Period25/03/2131/03/21

NREL Publication Number

  • NREL/CP-2C00-80343

Keywords

  • Gauss-Seidel smoother
  • inner-outer iterations
  • Krylov solver
  • MGS-GMRES
  • Neumann series

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