PyParSVD: A Streaming, Distributed and Randomized Singular-Value-Decomposition Library

Workshop:DRBSD-7: The 7th International Workshop on Data Analysis and Reduction for Big Scientific Data

Authors: Romit Maulik (Argonne National Laboratory (ANL), Illinois Institute of Technology) and Gianmarco Mengaldo (National University of Singapore)

Abstract: We introduce 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. Furthermore, 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.

https://github.com/Romit-Maulik/PyParSVD

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