Parallel Computing of Neural Network Algorithm for Fixed Channel Assignment Problem in Cellular Radio Networks with CUDA

DOI

抄録

In recent years, graphics processing units (GPUs) have been used for faster numerical calculation because they have many cores and can calculatevia parallel computing. In this paper, we propose a CUDA C program that aims to accelerate the extended maximum neural network algorithm for the fixed channel assignment problem (FCAP) in cellular radio networks using a general-purpose GPU (GPGPU). We evaluate the developed program using the existing benchmark problem in the FCAP. Results show that the processing speed of the developed program is 2.4 times to 15.1 times faster than in the case of using only a CPU.

収録刊行物

  • IEICE Proceeding Series

    IEICE Proceeding Series 29 720-723, 2017-12-04

    The Institute of Electronics, Information and Communication Engineers

キーワード

詳細情報 詳細情報について

  • CRID
    1390564227310431232
  • NII論文ID
    230000009479
  • DOI
    10.34385/proc.29.c2l-e-2-1
  • ISSN
    21885079
  • 本文言語コード
    en
  • データソース種別
    • JaLC
    • CiNii Articles
  • 抄録ライセンスフラグ
    使用不可

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