RSVDPACK: Subroutines for computing partial singular value decompositions via randomized sampling on single core, multi core, and GPU architectures
arXiv:1502.05366 [math.NA], (18 Feb 2015)
@article{voronin2015rsvdpack,
title={RSVDPACK: Subroutines for computing partial singular value decompositions via randomized sampling on single core, multi core, and GPU architectures},
author={Voronin, Sergey and Martinsson, Per-Gunnar},
year={2015},
month={feb},
archivePrefix={"arXiv"},
primaryClass={math.NA}
}
This document describes an implementation in C of a set of randomized algorithms for computing partial Singular Value Decompositions (SVDs). The techniques largely follow the prescriptions in the article "Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions," N. Halko, P.G. Martinsson, J. Tropp, SIAM Review, 53(2), 2011, pp. 217-288, but with some modifications to improve performance. The codes implement a number of low rank SVD computing routines for three different sets of hardware: (1) single core CPU, (2) multi core CPU, and (3) massively multicore GPU.
February 22, 2015 by hgpu
