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Accelerating Soft-Decision Reed-Muller Decoding Using a Graphics Processing Unit

Accelerating Soft-Decision Reed-Muller Decoding Using a Graphics Processing Unit

The Reed-Muller code is one of the efficient algorithms for multiple bit error correction, however, its high-computation requirement inherent in the decoding process prohibits its use in practical applications. To solve this problem, this paper proposes a graphics processing unit (GPU)-based parallel error control approach using Reed-Muller R(r, m) coding for real-time wireless communication systems. GPU offers a high-throughput parallel computing platform that can achieve the desired high-performance decoding by exploiting massive parallelism inherent in the algorithm. In addition, we compare the performance of the GPU-based approach with the equivalent sequential approach that runs on the traditional CPU. The experimental results indicate that the proposed GPU-based approach exceedingly outperforms the sequential approach in terms of execution time, yielding over 70× speedup.

1. Introduction

2. Proposed Approach

3. GPU-based Implementation of the Decoder of Reed-Muller Code

4. Experimental Results

5. Conclusions

References

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