Abstract

The Deflate compression algorithm provides one of the most widely used solutions for lossless data compression. Field-programmable gate arrays (FPGAs) are commonly used to implement hardware accelerators that speed up computation-intensive applications. In this article, FPGA-based accelerators for Deflate compression and decompression are described. These accelerators were specified in C++ and synthesized using Vivado High-Level Synthesis (HLS) for a Xilinx Virtex UltraScale+ series FPGA and a system clock frequency of 250 MHz. The proposed compressor processes data at a fixed input throughput of 4.0 GB/s and achieves a geometric mean compression ratio of 1.92 on the Calgary corpus benchmark files using static Huffman encoding. While not the first compressor synthesized using high-level synthesis, our design achieves a 25% greater throughput and an 11% greater compression ratio than the only other published design that uses Vivado HLS. The proposed decompressor design achieves average input throughputs of 196.61 MB/s and 97.40 MB/s, for statically and dynamically encoded Calgary corpus files, respectively. This is the first published decompressor design that is synthesized using high-level synthesis and provides performance that is comparable to that of the best published designs, having static throughputs 11% higher and dynamic throughputs only 10% lower than the expertly-optimized design sold by Xilinx.

Highlights

  • Data compression enables more efficient utilization of fixed data communication bandwidth and storage space

  • INFORMATION ON DEFLATE Deflate is the concatenation of two other compression algorithms: byte-level compression using LZ77 encoding [5] followed by bit-level compression using Huffman encoding [6]

  • COMPRESSOR RESULTS Our compressor core was implemented on a Xilinx XCVU3PFFVC1517 Virtex UltraScale+ Field-programmable gate arrays (FPGAs) [28]

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Summary

INTRODUCTION

Data compression enables more efficient utilization of fixed data communication bandwidth and storage space. We propose a compressor design that compresses data at a fixed input throughput of 4.0 GB/s while achieving a geometric mean compression ratio of 1.92 across the widely used Calgary corpus benchmark files [3] using static Huffman encoding. We propose a decompressor design with average input decompression throughputs of 196.61 MB/s and 97.40 MB/s, for statically and dynamically encoded Calgary corpus files, respectively These values are higher than most other reported decompressors while being achieved for the first time using high-level synthesis. This article is structured as follows: Section II reviews the Deflate file format and the compression and decompression processes.

BACKGROUND
PROPOSED COMPRESSOR DESIGN
PROPOSED DECOMPRESSOR DESIGN
CONCLUSION
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