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Fast matrix-vector multiplication in the sparse-grid Galerkin method. (English) Zbl 1231.65224
Summary: Sparse grid discretization of higher dimensional partial differential equations is a means to break the curse of dimensionality. For classical sparse grids based on the one-dimensional hierarchical basis, a sophisticated algorithm has been devised to calculate the application of a vector to the Galerkin matrix in linear complexity, despite the fact that the matrix is not sparse. However more general sparse grid constructions have been recently introduced, e.g. based on multilevel finite elements, where the specified algorithms only have a log-linear scaling. This article extends the idea of the linear scaling algorithm to more general sparse grid spaces. This is achieved by abstracting the algorithm given by R. Balder and Ch. Zenger [SIAM J. Sci. Comput. 17, No. 3, 631–646 (1996; Zbl 0855.65111)] from specific bases, thereby identifying the prerequisites for performing the algorithm. In this way one can easily adapt the algorithm to specific discretizations, leading for example to an optimal linear scaling algorithm in the case of multilevel finite element frames.

65N30 Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs
Full Text: DOI
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