PARALLEL NON-BINARY LDPC-DECODING ON THE GRAPHICS PROCESSOR
In this paper we propose a massively parallel implementation of the non-binary LDPC decoder based on the gras-Graphical processor (GPU) to achieve greater flexibility and scalability. Implementation displays algo-rhythm Min-Max decoding GPU parallel architecture. It describes the methodology of separating the decoding task on a heterogeneous platform consisting of a CPU and graphically gras-processor. Experimental results show that the decoder implementation based graphics processor achieves high throughput while providing more flexibility and scalability. The proposed architecture was implemented using OpenCL. This implementation is flexible and can be easily adjusted by adjusting the parameters to support different types of code, code length. Used half (620; 310) (3; 6) - regular GF (32) LDPC code, which is widely used in related research, and shows good performance error correction. Pre-representation method takes full advantage of graphics processors to speed up the processing power of non-binary LDPC decoding algorithms. The experimental results show that the proposition-adjoint non-binary low-density decoder based on the implementation of the graphics processor ustroytvo can achieve high performance, flexibility and scalability.