Work

Optimized Snappy Compression with Enhanced Encoding Strategies for Efficient FPGA Implementation

Year: 2025

Type: article

Abstract: The extensive utilization of the Snappy compression algorithm in digital devices such as smartphones, IoT, and digital cameras has played a crucial role in alleviating demands on network bandwidth and storage space. This paper presents an improved Snappy compression algorithm optimized for implementation on field programmable gate arrays (FPGAs). The proposed algorithm enhances the compression ratio by refining the encoding format of Snappy and introduces an innovative approach utilizing fingerprints within the dictionary to minimize storage space requirements. Additionally, the algorithm incorporates a pipeline structure to optimize performance. Experimental results demonstrate that the proposed algorithm achieves a throughput of 1.6 GB/s for eight hardware kernels. The average compression ratio is 2.27, representing a 6.1% improvement over the state-of-the-art Snappy FPGA implementation. Notably, the proposed algorithm architecture consumes fewer on-chip storage resources compared to other advanced algorithms, striking a balance between logic and storage resource utilization. This optimization leads to higher FPGA resource utilization efficiency. Our design addresses the growing demand for efficient lossless data compression solutions in consumer electronics, ultimately contributing to advancements in modern digital ecosystems.

Source: Electronics

DOI: 10.3390/electronics14152987

Authors: Huan Zhang, Chenpu Li, Meiting Xue, Bei Zhao, Jianrong Bao

Institutions: Hangzhou Dianzi University, Southeast University

Language: English

Topic: Algorithms and Data Compression

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,896