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Communication Dans Un Congrès Année : 2015

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.
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Dates et versions

hal-01255724 , version 1 (15-01-2016)

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  • HAL Id : hal-01255724 , version 1

Citer

Pierre Blanchard, Olivier Coulaud, E Darve, B Bramas. Hierarchical Randomized Low-Rank Approximations: Applications to covariance kernel matrices and generation of Gaussian Random Fields. SIAM Conference on Applied Linear Algebra (SIAM LA), SIAM, Oct 2015, Atlanta, United States. ⟨hal-01255724⟩
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