high performance computing on graphics processing units: hgpu.org

In this paper, we report a fast implementation of Wyner-Ziv video decoder using general-purpose computing on graphics processing units (GPGPU). Despite of its many advantages, Wyner-Ziv video coding has a problem of huge decoding complexity. Since Slepian-Wolf decoding with rate adaptive LDPC accumulate code takes up more than 90% of entire Wyner-Ziv video decoding complexity, in this paper, we focus on fast implementation of the Slepian-Wolf decoder using the CUDA (Compute Unified Device Architecture) which is a GPGPU architecture developed by NVIDIA. Our implementation is shown to be 4~5 times (QCIF size) or 15~20 times (CIF size) faster compared to conventional Slepian-Wolf decoding.