| 摘要 |
A method for utilizing a CUDA based GPU to accelerate a complex, sequential task such as video decoding, comprises decoding on a CPU headers and macroblocks of encoded video, performing inverse quantization (on CPU or GPU), transferring the picture data to GPU, where it is stored in a global buffer, and then on the GPU performing inverse waveform transforming of the inverse quantized data, performing motion compensation, buffering the reconstructed picture data in a GPU global buffer, determining if the decoded picture data are used as reference for decoding a further picture, and if so, copying the decoded picture data from the GPU global buffer to a GPU texture buffer. Advantages are that the data communication between CPU and GPU is minimized, the workload of CPU and GPU is balanced and the modules off-loaded to GPU can be efficiently realized since they are data-parallel and compute-intensive. |
