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

机译:不同核心处理器运动估计的并行全搜索算法的实现

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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:为了加速H.264 / AVC编码效率,本文提出了一种通过计算统一设备架构(CUDA)对图形处理器单元(GPU)的运动估计的完整搜索(FS)算法的并行化方法。 根据不同宏块(MBS)之间的独立性,我们将传统的顺序FS算法映射到CUDA并行计算模型的运动估计,利用优化内存使用,充分利用强大的并行计算能力来加速FS运动估计。 实验结果表明,我们在CUDA上的实施显着提高了高达50倍的CPU对应于可用的50倍,并且可以有效地加速FS运动估计。

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