Hierarchical Approximate Proper Orthogonal Decomposition ∗

@inproceedings{Himpe2018HierarchicalAP,
  title={Hierarchical Approximate Proper Orthogonal Decomposition ∗},
  author={Christian Himpe and Tobias Leibner and Stephan Rave},
  year={2018}
}
Proper Orthogonal Decomposition (POD) is a widely used technique for the construction of low-dimensional approximation spaces from highdimensional input data. For large-scale applications and an increasing number of input data vectors, however, computing the POD often becomes prohibitively expensive. This work presents a general, easy-to-implement approach to compute an approximate POD based on arbitrary tree hierarchies of worker nodes, where each worker computes a POD of only a small number… CONTINUE READING

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