Parallel computing platforms integrating CPU cores and mass of GPU accelerators have established in several application domains, obtaining remarkable time saving. In this way, video decoders can exploit a broader design space, to take full advantages of the hybrid GPU and CPU computing framework. Several novel contributions that aim at the exploitation of the maximum parallelism level in an AVS2 filtering optimization are presented: (1) a highly optimized GPU parallel implementation of video decoder, (2) the first known GPU implementation of the AVS2 loop filtering including deblocking'C SAO and ALF, (3) utilizing the available resources cooperatively by a hybrid CPU+GPU design. In this way, we obtained an experimental results coming out of speed-up factors as high as 22 for AVS2 loop filtering.
['Songyi Li', 'Ronggang Wang', 'Kaili Yao']
CUDA Acceleration for AVS2 Loop Filtering