DOI

The method of constructing a schedule for parallel algorithm execution is considered in the article. This algorithm takes into account the execution time of each operation of the algorithm and the relationship of operations on the data. The method is based on an information graph in which the nodes are the operations of the algorithm, and the edges are the directions of the data transfer. As a result of the interchange of operations between computing nodes, it is possible to achieve a reduction in the execution time of the algorithm by reducing the time spent on data transfer between computing nodes and reducing the downtime of computational nodes. The algorithm can be applied both in parallel programming and in adjacent areas, for example, when scheduling tasks in distributed systems.
Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2018
Subtitle of host publication18th International Conference, Melbourne, VIC, Australia, July 2–5, 2018, Proceedings, Part IV
PublisherSpringer Nature
Pages61-77
ISBN (Electronic)978-3-319-95171-3
ISBN (Print)978-3-319-95170-6
DOIs
StatePublished - 2018
Event18th International Conference on Computational Science and Its Applications, ICCSA 2018 - Melbourne, Australia
Duration: 2 Jul 2018 → 5 Jul 2018

Publication series

NameLecture Notes in Computer Science
Volume10963
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Computational Science and Its Applications, ICCSA 2018
Country/TerritoryAustralia
CityMelbourne
Period2/07/18 → 5/07/18

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

    Research areas

  • Algorithm execution schedule, Algorithm optimization, Information graph, Interprocessor data transmission, Operation execution time, Parallel algorithm, Process, Processor

ID: 30495447