TY - JOUR
T1 - Multi-level minimal residual smoothing
T2 - A family of general purpose multigrid acceleration techniques
AU - Zhang, Jun
N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 1998/11/30
Y1 - 1998/11/30
N2 - We employ multi-level minimal residual smoothing (MRS) as a pre-optimization technique to accelerate standard multigrid convergence. The MRS method is used to improve the current multigrid iterate by smoothing its corresponding residual before the latter is projected to the coarse grid. We develop different schemes for implementing MRS technique on the finest grid and on the coarse grids, and several versions of the inexact MRS technique. Numerical experiments are conducted to show the efficiency of the multi-level and inexact MRS techniques.
AB - We employ multi-level minimal residual smoothing (MRS) as a pre-optimization technique to accelerate standard multigrid convergence. The MRS method is used to improve the current multigrid iterate by smoothing its corresponding residual before the latter is projected to the coarse grid. We develop different schemes for implementing MRS technique on the finest grid and on the coarse grids, and several versions of the inexact MRS technique. Numerical experiments are conducted to show the efficiency of the multi-level and inexact MRS techniques.
KW - Minimal residual smoothing
KW - Multigrid method
KW - Residual scaling techniques
UR - http://www.scopus.com/inward/record.url?scp=0032203044&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0032203044&partnerID=8YFLogxK
U2 - 10.1016/S0377-0427(98)00133-2
DO - 10.1016/S0377-0427(98)00133-2
M3 - Article
AN - SCOPUS:0032203044
SN - 0377-0427
VL - 100
SP - 41
EP - 51
JO - Journal of Computational and Applied Mathematics
JF - Journal of Computational and Applied Mathematics
IS - 1
ER -