pLPAQ: Accelerating LPAQ Compression on FPGA
Journal
FPT 2022 - 21st International Conference on Field-Programmable Technology, Proceedings
ISBN
9781665453363
Date Issued
2022-01-01
Author(s)
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.
Subjects
Data Compression | FPGA | LPAQ
Type
conference paper