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'''Multigrid''' ('''MG''') '''methods''' in [[numerical analysis]] are fast linear iterative solvers based on the multilevel or multi-scale paradigm. The typical application for multigrid is in the numerical solution of [[elliptic partial differential
MG can be applied in combination with any of the common discretization techniques. In these cases, multigrid is among the fastest solution techniques known today. In contrast to other methods, multigrid is general in that it can treat arbitrary regions and [[boundary In all these cases, multigrid exhibits a convergence rate that is independent of the number of unknowns in the discretized system. It is therefore an optimal method. In combination with nested iteration it can solve these problems to truncation error accuracy in a number of operations that is proportional to the number of unknowns.
Multigrid can be generalized in many different ways. It can be applied naturally in a time
Other extensions of multigrid include techniques where no PDE and no geometrical problem background is used to construct the multilevel hierarchy. Such algebraic multigrid methods (AMG) construct their hierarchy of operators directly from the system matrix and thus become true black box solvers for sparse matrices.▼
▲Other extensions of multigrid include techniques where no PDE and no geometrical problem background is used to construct the multilevel hierarchy. Such '''algebraic multigrid methods''' (AMG) construct their hierarchy of operators directly from the system matrix and thus become true black
[[Category:Numerical analysis]]
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