Parallel Algorithmic Optimization for Enhanced Quasi-Maximum Likelihood Decoding on GPU

The Enhanced quasi-maximum likelihood (EQML) decoder has better decoding performance than the traditional belief propagation (BP) decoder, but its decoding speed is greatly reduced due to its complicated computational structure. Therefore, an efficient graphics processing unit (GPU) implementation structure for EQML decoder of low-density parity-check (LDPC) code is proposed. Intra-codeword parallel and inter-codeword parallel decoding schemes on GPU are adopted instead of serial decoding on CPU. Several optimization methods have also been employed to enhance the decoder throughput, such as compressed storing and Kernel thread arrangement scheme, which improve the decoding speed without degrading the decoding performance of the decoder. Experiment results show that our GPU based implementation structure which is about two orders of magnitude faster than that of CPU implementation.