A genetic algorithm for scheduling tasks onto dynamically reconfigurable hardware

Yang Qu, Juha-Pekka Soininen, Jari Nurmi

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

    9 Citations (Scopus)

    Abstract

    In this paper, a genetic algorithm (GA) for scheduling tasks onto dynamically reconfigurable devices is presented. The scheduling problem is NP-hard and more complicated than multiprocessor scheduling, because both the task allocation and the configurations need to be carefully managed. The approach has been validated with a number of random task graphs. The results show that the GA approach has good convergence and it is in average 8.6% better than a list-based scheduler for large task graphs of various sizes.
    Original languageEnglish
    Title of host publicationProceedings
    Subtitle of host publicationIEEE International Symposium on Circuits and Systems, ISCAS 2007
    Pages161-164
    DOIs
    Publication statusPublished - 2007
    MoE publication typeA4 Article in a conference publication
    EventIEEE International Symposium on Circuits and Systems, ISCAS 2007 - New Orleans, LA, United States
    Duration: 27 May 200730 May 2007

    Conference

    ConferenceIEEE International Symposium on Circuits and Systems, ISCAS 2007
    Abbreviated titleISCAS 2007
    CountryUnited States
    CityNew Orleans, LA
    Period27/05/0730/05/07

    Keywords

    • run-time reconfigurable hardware, genetic algorithm
    • task scheduling

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