A multigrid tutorial (2nd ed.)
A multigrid tutorial (2nd ed.)
A Multigrid Method Enhanced by Krylov Subspace Iteration for Discrete Helmholtz Equations
SIAM Journal on Scientific Computing
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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.