Parallel implementation of the CCSDS turbo decoder on GPU

Abstract

This paper presents a software turbo decoder on graphics processing units (GPU). Unlike previous works, the proposed decoding architecture for turbo codes mainly focuses on the Consultative Committee for Space Data Systems (CCSDS) standard. However, the information frame lengths of the CCSDS turbo codes are not suitable for flexible sub-frame parallelism design. To mitigate this issue, we propose a padding method that inserts several bits before the information frame header. To obtain low-latency performance and high resource utilization, two-level intra-frame parallelisms and an efficient data structure are considered. The presented Max-Log-Map decoder can be adopted to decode the Long Term Evolution (LTE) turbo codes with only small modifications. The proposed CCSDS turbo decoder at 10 iterations on NVIDIA RTX3070 achieves about 150 Mbps and 50 Mbps throughputs for the code rates 1/6 and 1/2, respectively.