Improving performance of GPU-based software beamforming using transform-based channel data compression

U. Lok, Pai-Chi Li
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引用次数: 2

Abstract

The massive data transfer of ultrasound data becomes a critical issue of real time transmission for a GPU-based beamformer. Our previous study proposed a real time lossless compression/decompression algorithm to truncate unnecessary bits of ultrasound baseband data and provided compression ratio around 1.7. The compression ability of the previous method depends on the largest signal within a batch, if the location of the largest signal within a batch can be identified and suppressed; higher compression ratio can be achieved. Therefore, we propose the use of the fast Walsh transform (FWT) associated with the lossless compression method to suppress amplitude data to enhance the compression ability of the lossless compression approach. From the simulation results, the compression ratios and PSNRs reached nearly 2.1-2.7 and 42-48 dB, respectively. The extra processing times for FWT performed in hardware front end required several clock cycles. In addition, the inverse FWT of a frame data implemented in a GPU required several milliseconds only. These results show that FWT accompany with the lossless compression method can effectively compress data with reasonable latency. The proposed compression method is also embedded in a 64 channel ultrasound imaging system to verify the feasibility for a GPU-based beamforming system.
利用基于变换的信道数据压缩提高基于gpu的软件波束形成性能
超声数据的大量传输成为基于gpu的波束形成器实时传输的关键问题。我们之前的研究提出了一种实时无损压缩/解压缩算法来截断不必要的超声基带数据位,压缩比约为1.7。前一种方法的压缩能力取决于批内最大的信号,如果能识别并抑制批内最大信号的位置;可以实现更高的压缩比。因此,我们提出将快速沃尔什变换(FWT)与无损压缩方法相结合,对振幅数据进行抑制,以增强无损压缩方法的压缩能力。从仿真结果来看,压缩比和psnr分别接近2.1 ~ 2.7和42 ~ 48 dB。在硬件前端执行FWT的额外处理时间需要几个时钟周期。此外,在GPU中实现的帧数据的逆FWT只需要几毫秒。实验结果表明,将FWT与无损压缩方法相结合,可以在合理的时延下有效压缩数据。将所提出的压缩方法嵌入到一个64通道超声成像系统中,以验证基于gpu的波束形成系统的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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