Sequential optimization of matrix chain multiplication relative to different cost functions

Igor Chikalov, Shahid Hussain, Mikhail Moshkov

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

10 Scopus citations

Abstract

In this paper, we present a methodology to optimize matrix chain multiplication sequentially relative to different cost functions such as total number of scalar multiplications, communication overhead in a multiprocessor environment, etc. For n matrices our optimization procedure requires O(n 3) arithmetic operations per one cost function. This work is done in the framework of a dynamic programming extension that allows sequential optimization relative to different criteria. © 2011 Springer-Verlag Berlin Heidelberg.
Original languageEnglish (US)
Title of host publicationSOFSEM 2011: Theory and Practice of Computer Science
PublisherSpringer Nature
Pages157-165
Number of pages9
ISBN (Print)9783642183805
DOIs
StatePublished - 2011

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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