Hierarchical Randomized Low-Rank Approximations
Résumé
We propose a new efficient algorithm for performing hierarchical kernel MVPs in O(N) operations called the Uniform FMM (UFMM), an FFT accelerated variant of the black-box FMM by Fong and Darve. The UFMM is used to speed-up randomized low-rank methods thus reducing their computational cost to O(N) in time and memory. Numerical benchmarks include low-rank approximations of covariance matrices for the simulation of stationary random fields on very large distributions of points.
Origine | Fichiers produits par l'(les) auteur(s) |
---|