Lossless Compression with Parallel Decoder for Improving Performance of a GPU-based Beamformer

A real time GPU-based beamformer suffers from large transmission bandwidth requirement to transfer massive ultrasound data from hardware front end to software back end system and the long processing time of memory copy from CPU to GPU. Data compression with sequential decoder can reduce the data size of ultrasound data but the time-consuming decompression process degrades the performance of data transfer in a GPU. Therefore, a lossless compression associated with fully parallel decoding scheme on graphics processing units (GPU) is proposed in this study to mitigate the transmission bandwidth of hardware interface, and is used to reduce the overall processing time of data transfers in a GPU. In our simulations, the compression ratio reached around 3 to 4 by combining demodulation, decimation and our proposed lossless compression. Consequently, the transmission bandwidth to transfer data from hardware to software system has nearly four-folded reduction. In addition, the simulation results showed that the processing times of data transfer of compressed data with parallel decoding process in a GPU has around three-folded improvement relative to transferring the original uncompressed data. These results show that our proposed lossless compression method with parallel decoder can improve the performance of data transfer in a GPU-based beamformer.