@inproceedings{bd6b7d026d0d42829babbcb33d13abd8,
title = "Hardware-oriented succinct-data-structure based on block-size-constrained compression",
abstract = "Succinct data structures are introduced to efficiently solve a given problem while representing the data using as little space as possible. However, the full potential of the succinct data structures have not been utilized in software-based implementations due to the large storage size and the memory access bottleneck. This paper proposes a hardware-oriented data compression method to reduce the storage space without increasing the processing time. We use a parallel processing architecture to reduce the decompression overhead. According to the evaluation, we can compress the data by 37.5% and still have fast data access with small decompression overhead.",
keywords = "big-data, data compression, FPGA, Succinct data structures, text-search",
author = "Waidyasooriya, {Hasitha Muthumala} and Daisuke Ono and Masanori Hariyama",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015 ; Conference date: 13-11-2015 Through 15-11-2015",
year = "2016",
month = jun,
day = "15",
doi = "10.1109/SOCPAR.2015.7492797",
language = "English",
series = "Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "136--140",
editor = "Mario Koppen and Muda, {Azah Kamilah} and Kun Ma and Bing Xue and Hideyuki Takagi and Ajith Abraham",
booktitle = "Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015",
address = "United States",
}