3.8-Gbps Polar Belief Propagation Decoder on GPU

In this work, a high-throughput belief propagation (BP) decoder of polar codes on graphics processing unit (GPU) is proposed for software-defined communication systems. The decoder is jointly optimized from algorithm and architecture aspects. From the algorithm aspect, the storage pattern and computation flow are optimized to reduce complexity. From the architecture aspect, different granularities of parallelism are extensively exploited to achieve high throughput. Equipped with these techniques, a high-speed GPU-based BP decoder is developed, and experimental results show that the proposed decoder can improve the normalized throughput by 64.1% to 294.1% compared to the state-of-the-art GPU-based BP decoder.