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Reseach Article

DKLZSS - A Dynamic KMP String Matching Method for Parallel LZSS Compression on GPGPUs

Published on June 2016 by Vaibhav Tulsyan, Aditya Sarode, Aaryaman Vasishta, Tarun Notani, A. R. Sharma
National Conference on Advances in Computing, Communication and Networking
Foundation of Computer Science USA
ACCNET2016 - Number 2
June 2016
Authors: Vaibhav Tulsyan, Aditya Sarode, Aaryaman Vasishta, Tarun Notani, A. R. Sharma
ba9705b4-c2ed-4ab7-9f97-73f8ef6eef8f

Vaibhav Tulsyan, Aditya Sarode, Aaryaman Vasishta, Tarun Notani, A. R. Sharma . DKLZSS - A Dynamic KMP String Matching Method for Parallel LZSS Compression on GPGPUs. National Conference on Advances in Computing, Communication and Networking. ACCNET2016, 2 (June 2016), 5-8.

@article{
author = { Vaibhav Tulsyan, Aditya Sarode, Aaryaman Vasishta, Tarun Notani, A. R. Sharma },
title = { DKLZSS - A Dynamic KMP String Matching Method for Parallel LZSS Compression on GPGPUs },
journal = { National Conference on Advances in Computing, Communication and Networking },
issue_date = { June 2016 },
volume = { ACCNET2016 },
number = { 2 },
month = { June },
year = { 2016 },
issn = 0975-8887,
pages = { 5-8 },
numpages = 4,
url = { /proceedings/accnet2016/number2/24975-2263/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advances in Computing, Communication and Networking
%A Vaibhav Tulsyan
%A Aditya Sarode
%A Aaryaman Vasishta
%A Tarun Notani
%A A. R. Sharma
%T DKLZSS - A Dynamic KMP String Matching Method for Parallel LZSS Compression on GPGPUs
%J National Conference on Advances in Computing, Communication and Networking
%@ 0975-8887
%V ACCNET2016
%N 2
%P 5-8
%D 2016
%I International Journal of Computer Applications
Abstract

Fast data compression is gaining increasing importance in the re- cent times. Statistical compression methods and methods pertain- ing to textual substitution have been studied in great detail in the last few decades, however, the problem of compressing data at very high speeds with less compression trade-off still remains un- solved to a certain extent. General Purpose Graphic Processing Units (GPGPUs) are a powerful tool that allow large-scale parallel processing, owing to a large number of Streaming Multiprocessors. Recent studies on parallel methods for compression using tex- tual substitution show that considerable speed-ups can be obtained by using the Lempel-Ziv-Storer-Szymanski(LZSS)[9] lossless data compression algorithm on GPUs. In this paper, a parallel, space- efficient compression algorithm using GPGPUs for LZSS com- pression, along with a dynamic variation of the Knuth-Morris-Pratt (KMP) string-matching algorithm[2] is presented. The algorithm splits the input data into disjoint data chunks and performs com- pression on each chunk using the Dynamic KMP algorithm, inde- pendent of the compression of other chunks.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Lzss kmp culzss gpu gpu