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This paper presents a computationally efficient implementation of a Hammingcode decoder on a graphics processing unit (GPU) to support real-timesoftware-defined radio (SDR), which is a software alternative for realizingwireless communication. The Hamming code algorithm is challenging toparallelize effectively on a GPU because it works on sparsely located dataitems with several conditional statements, leading to non-coalesced, longlatency, global memory access, and huge thread divergence. To address theseissues, we propose an optimized implementation of the Hamming code on the GPUto exploit the higher parallelism inherent in the algorithm. Experimentalresults using a compute unified device architecture (CUDA)-enabled NVIDIAGeForce GTX 560, including 335 cores, revealed that the proposed approachachieved a 99x speedup versus the equivalent CPU-based implementation.

Computationally Efficient Implementation of a Hamming Code Decoder using a Graphics Processing Unit