• DocumentCode
    3607595
  • Title

    High Throughput Pipeline Decoder for LDPC Convolutional Codes on GPU

  • Author

    Yi Hou ; Rongke Liu ; Hao Peng ; Ling Zhao

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Beihang Univ., Beijing, China
  • Volume
    19
  • Issue
    12
  • fYear
    2015
  • Firstpage
    2066
  • Lastpage
    2069
  • Abstract
    In this letter, we present a graphics processing unit (GPU)-based LDPC convolutional code (LDPC-CC) pipeline decoder with optimized parallelism. The proposed decoder exploits different granularities of decoding parallelism for both the compute unified device architecture (CUDA) kernel execution stage and the data transfer stage. Moreover, the parameter selection criteria for decoder implementation are designed to avoid exhaustive search of all the combinations of parameters. The experiments are carried out on Nvidia GTX460 and GTX580 platforms. The results demonstrate the proposed decoder achieves about 3 times speedup compared to the existing GPU-based work.
  • Keywords
    convolutional codes; decoding; graphics processing units; parity check codes; CUDA kernel execution stage; GPU; LDPC-CC pipeline decoder; Nvidia GTX460; Nvidia GTX580; compute unified device architecture; data transfer stage; decoding parallelism granularity; graphics processing unit; low-density parity check convolutional code; throughput pipeline decoder; Decoding; Graphics processing units; Iterative decoding; Parallel processing; Throughput; GPU; LDPC convolutional code; parallelism; pipeline decoder;
  • fLanguage
    English
  • Journal_Title
    Communications Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1089-7798
  • Type

    jour

  • DOI
    10.1109/LCOMM.2015.2486764
  • Filename
    7289356