FPGA Acceleration of Zstd Compression Algorithm
Jianyu Chen (Student TU Delft, Optiver)
Maurice Daverveldt (Optiver)
Zaid Al-Ars (TU Delft - Computer Engineering)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
With the continued increase in the amount of big data generated and stored in various application domains, such as high-frequency trading, compression techniques are becoming ever more important to reduce the requirements on communication bandwidth and storage capacity. Zstandard (Zstd) is emerging as an important compression algorithm for big data sets capable of achieving a good compression ratio but with a higher speed than comparable algorithms. In this paper, we introduce the architecture of a new hardware compression kernel for Zstd that allows the algorithm to be used for real-time compression of big data streams. In addition, we optimize the proposed architecture for the specific use case of streaming high-frequency trading data. The optimized kernel is implemented on a Xilinx Alveo U200 board. Our optimized implementation allows us to fit ten kernel blocks on one board, which is able to achieve a compression throughput of about 8.6GB/s and compression ratio of about 23.6%. The hardware implementation is open source and publicly available at https://github.com/ChenJianyunp/Hardware-Zstd-Compression-Unit.