Parallel Data Compression Techniques
David Noel, Elizabeth Graham, Liyuan Liu
TL;DR
This paper investigates methods to parallelize three data compression algorithms—Huffman coding, LZSS, and MP3—to improve speed on multi-core processors, addressing the challenge of inherent serial processing in compression tasks.
Contribution
It introduces novel techniques for parallelizing Huffman coding, LZSS, and MP3 compression algorithms to enhance their performance on multi-core systems.
Findings
Parallel Huffman coding achieves significant speedup
LZSS parallelization reduces compression time substantially
MP3 parallel processing maintains audio quality while increasing speed
Abstract
With endless amounts of data and very limited bandwidth, fast data compression is one solution for the growing datasharing problem. Compression helps lower transfer times and save memory, but if the compression takes too long, this no longer seems viable. Multi-core processors enable parallel data compression; however, parallelizing the algorithms is anything but straightforward since compression is inherently serial. This paper explores techniques to parallelize three compression schemes: Huffman coding, LZSS, and MP3 coding
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Taxonomy
TopicsAlgorithms and Data Compression · Advanced Data Compression Techniques