PyParSVD: A streaming, distributed and randomized singular-value-decomposition library
Mathematical Software
2021-08-23 v1 Distributed, Parallel, and Cluster Computing
Atmospheric and Oceanic Physics
Fluid Dynamics
Abstract
We introduce PyParSVD\footnote{https://github.com/Romit-Maulik/PyParSVD}, a Python library that implements a streaming, distributed and randomized algorithm for the singular value decomposition. To demonstrate its effectiveness, we extract coherent structures from scientific data. Futhermore, we show weak scaling assessments on up to 256 nodes of the Theta machine at Argonne Leadership Computing Facility, demonstrating potential for large-scale data analyses of practical data sets.
Keywords
Cite
@article{arxiv.2108.08845,
title = {PyParSVD: A streaming, distributed and randomized singular-value-decomposition library},
author = {Romit Maulik and Gianmarco Mengaldo},
journal= {arXiv preprint arXiv:2108.08845},
year = {2021}
}
Comments
arXiv admin note: text overlap with arXiv:2103.09389