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Multigrid Methods: Managing Massive Meshes
September/October 2006 (vol. 8 no. 5)
pp. 96-103
ASCII Text
x 
 
Dianne P. O'Leary, "Multigrid Methods: Managing Massive Meshes," Computing in Science and Engineering, vol. 8, no. 5, pp. 96-103, September/October, 2006.
 
 
BibTex
x
 
@article{ 10.1109/MCSE.2006.94,
author = {Dianne P. O'Leary},
title = {Multigrid Methods: Managing Massive Meshes},
journal ={Computing in Science and Engineering},
volume = {8},
number = {5},
issn = {1521-9615},
year = {2006},
pages = {96-103},
doi = {http://doi.ieeecomputersociety.org/10.1109/MCSE.2006.94},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - Computing in Science and Engineering
TI - Multigrid Methods: Managing Massive Meshes
IS - 5
SN - 1521-9615
SP96
EP103
EPD - 96-103
A1 - Dianne P. O'Leary,
PY - 2006
KW - multigrid
KW - finite element
KW - finite difference
VL - 8
JA - Computing in Science and Engineering
ER -
 
Dianne P. O'Leary, University of Maryland
In our last homework assignment, we investigated iterative methods for solving large, sparse, linear systems of equations. We saw that the Gauss-Seidel (GS) method was intolerably slow, but various forms of preconditioned conjugate gradient (CG) algorithms gave us reasonable results. The test problems we used were discretizations of elliptic partial differential equations, but for these problems, we can use a faster class of methods called multigrid algorithms.
Index Terms:
multigrid, finite element, finite difference
Citation:
Dianne P. O'Leary, "Multigrid Methods: Managing Massive Meshes," Computing in Science and Engineering, vol. 8, no. 5, pp. 96-103, Sep./Oct. 2006, doi:10.1109/MCSE.2006.94
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