Pipelined Parallel LZSS for Streaming Data Compression on GPGPUs

In this paper, we present an algorithm and provide design improvements needed to port the serial Lempel-Ziv-Storer-Szymanski (LZSS), lossless data compression algorithm, to a parallelized version suitable for general purpose graphic processor units (GPGPU), specifically for NVIDIA's CUDA Framew...

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Bibliographic Details
Published in2012 IEEE 18th International Conference on Parallel and Distributed Systems pp. 37 - 44
Main Authors Ozsoy, A., Swany, M., Chauhan, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2012
Subjects
Algorithm design and analysis
CUDA
Data compression
Encoding
GPU
Graphics processing units
History
Instruction sets
Lossless data compression
LZSS
Software algorithms
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Summary:In this paper, we present an algorithm and provide design improvements needed to port the serial Lempel-Ziv-Storer-Szymanski (LZSS), lossless data compression algorithm, to a parallelized version suitable for general purpose graphic processor units (GPGPU), specifically for NVIDIA's CUDA Framework. The two main stages of the algorithm, substring matching and encoding, are studied in detail to fit into the GPU architecture. We conducted detailed analysis of our performance results and compared them to serial and parallel CPU implementations of LZSS algorithm. We also benchmarked our algorithm in comparison with well known, widely used programs, GZIP and ZLIB. We achieved up to 34x better throughput than the serial CPU implementation of LZSS algorithm and up to 2.21x better than the parallelized version.
ISBN:9781467345651
1467345652
ISSN:1521-9097
2690-5965
DOI:10.1109/ICPADS.2012.16