Effective parallel algorithm for GPGPU-accelerated explicit routing optimization

Ko Kikuta, Eiji Oki, Naoaki Yamanaka, Nozomu Togawa, Hidenori Nakazato

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

    1 Citation (Scopus)

    Abstract

    The recent development of network technologies that offer centralized control of explicit routes opens the door to the online optimization of explicit routing. For this kind of Traffic Engineering optimization, raising the calculation speeds by using multi-core processors with effective parallel algorithms is a key goal. This paper proposes an effective parallel algorithm for General purpose Programming on Graphic Processing Unit (GPGPU); its massively parallel style promises strong acceleration of calculation speed. The proposed algorithm parallelizes not only the search method of the Genetic Algorithm, but also its fitness functions, which calculate the network congestion ratio, so as to fully utilize the power of modern GPGPUs. Concurrently, each execution is designed for thread-block execution on the GPU with consideration of thread occupancy, local resources, and SIMT execution to maximize GPU performance. Evaluations show that the proposed algorithm offers, on average, a nine fold speedup compared to the conventional CPU approach.

    Original languageEnglish
    Title of host publication2015 IEEE Global Communications Conference, GLOBECOM 2015
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Print)9781479959525
    DOIs
    Publication statusPublished - 2016 Feb 23
    Event58th IEEE Global Communications Conference, GLOBECOM 2015 - San Diego, United States
    Duration: 2015 Dec 62015 Dec 10

    Other

    Other58th IEEE Global Communications Conference, GLOBECOM 2015
    CountryUnited States
    CitySan Diego
    Period15/12/615/12/10

    Fingerprint

    Computer programming
    Parallel algorithms
    programming
    Program processors
    Genetic algorithms
    fitness
    Graphics processing unit
    traffic
    engineering
    evaluation
    resources
    performance

    Keywords

    • GPGPU
    • Optimization
    • Traffic engineering

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Electrical and Electronic Engineering
    • Communication

    Cite this

    Kikuta, K., Oki, E., Yamanaka, N., Togawa, N., & Nakazato, H. (2016). Effective parallel algorithm for GPGPU-accelerated explicit routing optimization. In 2015 IEEE Global Communications Conference, GLOBECOM 2015 [7416979] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOCOM.2014.7416979

    Effective parallel algorithm for GPGPU-accelerated explicit routing optimization. / Kikuta, Ko; Oki, Eiji; Yamanaka, Naoaki; Togawa, Nozomu; Nakazato, Hidenori.

    2015 IEEE Global Communications Conference, GLOBECOM 2015. Institute of Electrical and Electronics Engineers Inc., 2016. 7416979.

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

    Kikuta, K, Oki, E, Yamanaka, N, Togawa, N & Nakazato, H 2016, Effective parallel algorithm for GPGPU-accelerated explicit routing optimization. in 2015 IEEE Global Communications Conference, GLOBECOM 2015., 7416979, Institute of Electrical and Electronics Engineers Inc., 58th IEEE Global Communications Conference, GLOBECOM 2015, San Diego, United States, 15/12/6. https://doi.org/10.1109/GLOCOM.2014.7416979
    Kikuta K, Oki E, Yamanaka N, Togawa N, Nakazato H. Effective parallel algorithm for GPGPU-accelerated explicit routing optimization. In 2015 IEEE Global Communications Conference, GLOBECOM 2015. Institute of Electrical and Electronics Engineers Inc. 2016. 7416979 https://doi.org/10.1109/GLOCOM.2014.7416979
    Kikuta, Ko ; Oki, Eiji ; Yamanaka, Naoaki ; Togawa, Nozomu ; Nakazato, Hidenori. / Effective parallel algorithm for GPGPU-accelerated explicit routing optimization. 2015 IEEE Global Communications Conference, GLOBECOM 2015. Institute of Electrical and Electronics Engineers Inc., 2016.
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