International Conference on Consumer Electronics, Communications and Networks (CECNet)

Simulation of LDPC convolutional decoders with CPU and GPU

Chi Ho Chan, Francis C. M. Lau

Published Apr 1, 2012• 2 citations

Abstract

In this paper, the Sum Product Algorithm (SPA) and the Min-Sum Algorithm (MSA) are used for decoding low-density parity-check convolutional codes (LDPC-CCs). The two algorithms have been implemented and run on three different computing environments. The first environment is a single-threading Central Processing Unit (CPU); the second one is the multi-threading CPU based on OpenMP (Open Multi-Processing); and the third one is the multi-threading Graphics Processing Unit (GPU). The error performance of the LDPC-CCs and the simulation time taken under the three specific computing environments and the two decoding algorithms are evaluated and compared. It is found that the different computing environments produce very similar error results. It is also concluded that using the GPU computing platform can reduce the simulation time substantially.

DOI: 10.1109/cecnet.2012.6202062

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