Turbo Product Code (TPC) is a class of Forward Error Correction (FEC) codes that have good Bit Error Rate (BER) performance at high code rate. TPC is widely used in a variety of scenarios, such as satellite communication systems and data storage systems. This paper proposes a GPU-based parallel TPC decoder. In it, all rows or columns of the two-dimensional product code matrix can be translated at the same time. A parallel basic decoder is designed to simplify the decoding process of TPC consisting of extended Hamming code. The parallelization of test sample and effective code word calculation is realized, and the decoding delay is reduced. In order to further improve the decoding throughput, we propose a multi-channel TPC decoder. In addition, the performance of parallel decoders is measured on different GPUs. The experimental results show that the decoding delay of the GPU-based parallel decoder is significantly reduced compared with the CPU-based TPC decoder. In addition, the throughput of the GPU decoder reaches 30 Mbps on the Nvidia RTX 2080 Ti and 38 Mbps on the NVIDIA GTX Titan V, which is 44 times and 54 times the performance of the CPU-based decoder.

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