$p$LPAQ: Accelerating LPAQ Compression on FPGA

Dongdong Tang, Xuan Sun, Nan Guan, Tei-Wei Kuo, C. Xue
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Abstract

In recent years, the demand for data storage space has increased dramatically due to the exponential growth of data volume. Data compression is of great significance since it saves data storage space and reduces data transfer demand. Compression algorithms based on statistical models have a much higher compression ratio than dictionary-based methods, but the high computational time cost of statistical modeling limits their wider application. In this paper, we introduce pLPAQ, an FPGA-based design of a powerful compression algorithm LPAQ based on statistical models. A novel hardware accelerator is proposed to speed up LPAQ by fully utilizing the parallelism of FPGA. Experimental results show that the proposed design can achieve a throughput of 12 MB/s on Xilinx Virtex Plus UltraScale XCVU9P card, 25x faster than executing on AMD Ryzen R7 4800U at 2.8 GHz and 80x faster compared with the naive FPGA implementation on average.
在FPGA上加速LPAQ压缩
近年来,由于数据量呈指数级增长,对数据存储空间的需求急剧增加。数据压缩节省了数据存储空间,减少了数据传输需求,具有重要意义。基于统计模型的压缩算法具有比基于字典的方法高得多的压缩比,但统计建模的计算时间成本高,限制了其广泛应用。本文介绍了一种基于fpga的基于统计模型的强大压缩算法LPAQ的设计。为了充分利用FPGA的并行性,提出了一种新的硬件加速器来加速LPAQ。实验结果表明,该设计在Xilinx Virtex Plus UltraScale XCVU9P卡上可以实现12 MB/s的吞吐量,比在AMD Ryzen R7 4800U 2.8 GHz上执行快25倍,比原始FPGA实现平均快80倍。
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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