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Article | Open Access

Efficient OpenMP Based Z-curve Encoding and Decoding Algorithms

Zicheng Zhou1Shaowen Sun2Teng Liang3Mengjuan Li4( )Fengling Xia5( )
School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, China
School of Communications Information Engineering, Yunnan Communications Vocational and Technical College, Kunming, 650500, China
Library, Yunnan Normal University, Kunming, 650500, China
Faculty of Civil Aviation and Aeronautics, Kunming University of Science and Technology, Kunming, 650500, China
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Abstract

Z-curve’s encoding and decoding algorithms are primely important in many Z-curve-based applications. The bit interleaving algorithm is the current state-of-the-art algorithm for encoding and decoding Z-curve. Although simple, its efficiency is hindered by the step-by-step coordinate shifting and bitwise operations. To tackle this problem, we first propose the efficient encoding algorithm LTFe and the corresponding decoding algorithm LTFd, which adopt two optimization methods to boost the algorithm’s efficiency: 1) we design efficient lookup tables (LT) that convert encoding and decoding operations into table-lookup operations; 2) we design a bit detection mechanism that skips partial order of a coordinate or a Z-value with consecutive 0s in the front, avoiding unnecessary iterative computations. We propose order-parallel and point-parallel OpenMP-based algorithms to exploit the modern multi-core hardware. Experimental results on discrete, skewed, and real datasets indicate that our point-parallel algorithms can be up to 12.6× faster than the existing algorithms.

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Computers, Materials & Continua
Pages 1313-1327

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Cite this article:
Zhou Z, Sun S, Liang T, et al. Efficient OpenMP Based Z-curve Encoding and Decoding Algorithms. Computers, Materials & Continua, 2025, 82(1): 1313-1327. https://doi.org/10.32604/cmc.2024.056880

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Received: 01 August 2024
Accepted: 30 October 2024
Published: 31 January 2025
© The Author 2025.

This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.