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Implementation of parallel full search algorithm for motion estimation on multi-core processors

机译:并行全搜索算法在多核处理器上进行运动估计的实现

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In order to speed up H.264/AVC coding efficiency, this paper proposed a parallelization approach of full search (FS) algorithm for motion estimation on Graphic Processor Unit (GPU) using computing unified device architecture (CUDA). According to the independence among different macro-blocks (MBs), we mapped the traditional sequential FS algorithm for motion estimation to CUDA parallel computing model with optimizing memory usage, taking full advantage of the powerful parallel computing capability to speed up FS motion estimation. Experimental results show that our implementation on CUDA demonstrates substantial improvement up to 50 times than CPU counterpart available and can effectively speed up the FS for motion estimation.
机译:为了提高H.264 / AVC编码效率,本文提出了一种采用计算统一设备架构(CUDA)的全搜索(FS)算法在图形处理器单元(GPU)上进行运动估计的并行化方法。根据不同宏块之间的独立性,我们将传统的运动估计顺序FS算法映射到CUDA并行计算模型,并优化了内存使用,充分利用了强大的并行计算能力来加快FS运动估计。实验结果表明,我们在CUDA上的实现表明,与可用的CPU相比,可实现多达50倍的实质性改进,并且可以有效地加快运动估计的FS。

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