76.5-Gb/s Viterbi Decoder for Convolutional Codes on GPU

  • Zhanxian Liu
  • , Chufan Liu
  • , Haijun Zhang*
  • , Ling Zhao
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This letter presents an optimized Viterbi decoder of convolutional codes on graphics processing unit (GPU) for software defined radio (SDR) platforms. Before the forward process, channel messages are interleaved with coalesced global memory access and the interleaved messages are represented with 4 bits to improve shared memory efficiency. Moreover, we optimize on-chip memory allocations of the forward process to accelerate instruction execution. Excluding the data transfer latency between host and device, the proposed Viterbi decoder achieves 22.2 and 76.5-Gb/s throughput on Tesla V100 and RTX4090, respectively. Compared with related works, the throughput speedups achieved by the proposed decoder are from 2.06× to 2.93×.

Original languageEnglish
Pages (from-to)22-25
Number of pages4
JournalIEEE Embedded Systems Letters
Volume17
Issue number1
DOIs
StatePublished - 2025

Keywords

  • Convolutional code
  • Viterbi
  • graphics processing unit (GPU)
  • parallel decoding
  • software defined radio (SDR)

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