Abstract
The main contribution of this paper is to present a parallel algorithm for LZW decompression and to implement it in a CUDA-enabled GPU. Since sequential LZW decompression creates a dictionary table by reading codes in a compressed file one by one, its parallelization is not an easy task. We first present a parallel LZW decompression algorithm on the CREW-PRAM. We then go on to present an efficient implementation of this parallel algorithm on a GPU. The experimental results show that our parallel LZW decompression on GeForce GTX 980 runs up to 69.4 times faster than sequential LZW decompression on a single CPU. We also show a scenario that parallel LZW decompression on a GPU can be used for accelerating big data applications.
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Funasaka, S., Nakano, K., Ito, Y. (2016). A Parallel Algorithm for LZW Decompression, with GPU Implementation. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2015. Lecture Notes in Computer Science(), vol 9573. Springer, Cham. https://doi.org/10.1007/978-3-319-32149-3_22
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DOI: https://doi.org/10.1007/978-3-319-32149-3_22
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