High-Throughput and Memory-Efficient Parallel Viterbi Decoder for Convolutional Codes on GPU

TL;DR

This paper presents a GPU-based parallel Viterbi decoder that significantly improves throughput and memory efficiency for convolutional codes, enhancing wireless communication system performance.

Contribution

It introduces a novel parallel implementation with unified kernel and parallel traceback, optimizing both throughput and memory usage over existing GPU solutions.

Findings

Higher throughput than previous GPU solutions

Reduced memory usage through optimization

Effective parallel traceback implementation

Abstract

This paper describes a parallel implementation of Viterbi decoding algorithm. Viterbi decoder is widely used in many state-of-the-art wireless systems. The proposed solution optimizes both throughput and memory usage by applying optimizations such as unified kernel implementation and parallel traceback. Experimental evaluations show that the proposed solution achieves higher throughput compared to previous GPU-accelerated solutions.