PyParSVD: A streaming, distributed and randomized singular-value-decomposition library

Romit Maulik, Gianmarco Mengaldo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

We introduce PyParSVD11https://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.

Original languageEnglish (US)
Title of host publicationProceedings of DRBSD-7 2021
Subtitle of host publication7th International Workshop on Data Analysis and Reduction for Big Scientific Data, Held in conjunction with SC 2021: The International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages19-25
Number of pages7
ISBN (Electronic)9781728186726
DOIs
StatePublished - 2021
Event7th International Workshop on Data Analysis and Reduction for Big Scientific Data, DRBSD-7 2021 - St. Louis, United States
Duration: Nov 14 2021 → …

Publication series

NameProceedings of DRBSD-7 2021: 7th International Workshop on Data Analysis and Reduction for Big Scientific Data, Held in conjunction with SC 2021: The International Conference for High Performance Computing, Networking, Storage and Analysis

Conference

Conference7th International Workshop on Data Analysis and Reduction for Big Scientific Data, DRBSD-7 2021
Country/TerritoryUnited States
CitySt. Louis
Period11/14/21 → …

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Information Systems
  • Information Systems and Management
  • Statistics, Probability and Uncertainty
  • Media Technology

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