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An Accelerated H.264/AVC Encoder on Graphic Processing Unit for UAV Videos

机译:图形处理单元上用于无人机视频的加速H.264 / AVC编码器

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With regards to the nature of high intensive computation for motion estimation with an H.264/AVC encoder, this paper presents a parallel block-matching algorithm implemented on a general purpose graphics processing units (GPU) to speed up the execution of UAV video coding. Traditional parallel block-matching algorithms are primarily used to leverage the huge number of computational cores in graphic processing units, which can be used to compute the block-matching operation at each candidate position in a search range by an independent thread of kernel computation. In realistic scenarios, the time used to transfer pixel values among the various memory modules to fulfill the operation in a GPU system is much higher than the computation time used for computing each block-matching operation by the kernel threads. This leads to a performance improvement bottleneck for GPU algorithm design. The proposed algorithm exploits the characteristics of distinct memory modules on the data transfer speed for the block-matching algorithm and proposes a feasible mechanism to reduce the bandwidth of data transmission required for the parallel block-matching algorithms implemented on GPU system. With experiments on GPU systems, the proposed parallel block-matching algorithm gains up to 99% execution reduction of motion estimation compared to the host processor only motion estimation process.
机译:关于使用H.264 / AVC编码器进行运动估计的高强度计算的本质,本文提出了一种在通用图形处理单元(GPU)上实现的并行块匹配算法,以加快无人机视频编码的执行速度。传统的并行块匹配算法主要用于利用图形处理单元中的大量计算核,这些核可用于通过内核计算的独立线程在搜索范围内的每个候选位置计算块匹配操作。在实际情况下,用于在GPU系统中完成各个存储模块之间的像素值传输的时间比内核线程计算每个块匹配操作所用的计算时间高得多。这导致了GPU算法设计的性能改进瓶颈。所提出的算法利用了不同存储模块在块匹配算法的数据传输速度上的特性,并提出了一种可行的机制来减少在GPU系统上实现的并行块匹配算法所需的数据传输带宽。通过在GPU系统上进行的实验,与仅主机处理器的运动估计过程相比,提出的并行块匹配算法可将运动估计的执行减少多达99%。

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