Efficient evaluation of matrix polynomials

Niv Hoffman, Oded Schwartz, Sivan Toledo*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We revisit the problem of evaluating matrix polynomials and introduce memory and communication efficient algorithms. Our algorithms, based on that of Patterson and Stockmeyer, are more efficient than previous ones, while being as memory-efficient as Van Loan’s variant. We supplement our theoretical analysis of the algorithms, with matching lower bounds and with experimental results showing that our algorithms outperform existing ones.

Original languageAmerican English
Title of host publicationParallel Processing and Applied Mathematics - 12th International Conference, PPAM 2017, Revised Selected Papers
EditorsJack Dongarra, Roman Wyrzykowski, Konrad Karczewski, Ewa Deelman
PublisherSpringer Verlag
Pages24-35
Number of pages12
ISBN (Print)9783319780238
DOIs
StatePublished - 2018
Event12th International Conference on Parallel Processing and Applied Mathematics, PPAM 2017 - Czestochowa, Poland
Duration: 10 Sep 201713 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10777 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Parallel Processing and Applied Mathematics, PPAM 2017
Country/TerritoryPoland
CityCzestochowa
Period10/09/1713/09/17

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.

Keywords

  • Cache efficiency
  • Matrix polynomials
  • Polynomial evaluation

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