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Hardware-accelerated Fast Lossless Compression Based on LZ4 Algorithm

Published: 24 February 2019 Publication History

Abstract

Data compression can efficiently utilize the storage capacity. Especially for mobile devices, they have limited resources such as a CPU (Central Processing Unit) operation clock and a power source, so hardware designed compression method is required. Most adaptive dictionary-based compression methods have their root in Lempel-Ziv algorithm. LZ4 is one of the fastest compression algorithms. In this paper, we propose an advanced algorithm and hardware architecture with improved compression ratio and speed. In order to achieve a higher compression ratio, the proposed algorithm has a variable length format while LZ4 has a fixed length format. Experimental results show that the proposed architecture can achieve compression throughput up to 3.84Gbps and compression ratio up to 4. In this way, our hardware-based architecture improves memory performance and battery life of mobile devices with low power consumption.

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Sayood, K. 2017. Introduction to Data Compression (5th ed), Morgan Kaufmann, Burlington, MA.
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Huffman, D.A. 1952. A method for the construction of minimum redundancy codes. Proceedings of the IRE, 40, 1098--1101.
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Witten, I.H., Neal, R.M. and Cleary, J.G. 1987. Arithmetic coding for data compression. Communications of the ACM, 30(6), 520--540.
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Ziv, J. and Lempel, A. 1977. A universal algorithm for sequential data compression, IEEE transaction on information theory, 23(3), 337--343.
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Ziv, J. and Lempel, A. 1978. A compression of individual sequences via variable-rate coding. IEEE transaction on information theory, 24(5), 530--536.
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Bartik, M., Ubik, S. and Kubalik, P. LZ4 compression algorithm on FPGA. 2015. In International Conference on Electronics, Circuits, and System, (Cairo, Egypt), IEEE Publishers, 179--182.
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Liu, W. Data Compression Device Based on Modified LZ4 Algorithm. 2018. IEEE transaction on consumer electronics, 64(1), 110--117.
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Collet, Y. 2011. Real Time Data Compression: LZ4 Explained. https://github.com/lz4/lz4.
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Rigler, S., Bishop, W. and Kennings, A. 2007. FPGA-Based Lossless Data Compression using Huffman and LZ77 Algorithms, In Canadian Conference on Electrical and Computer Engineering, (Vancouver, BC, Canada), IEEE Publishers, 1235--1238.
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Cited By

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  • (2024)GCC: Optimizing Space Efficiency and Read Latency of SSDs with Workload-Aware Garbage Collection Aided Compression2024 IEEE 42nd International Conference on Computer Design (ICCD)10.1109/ICCD63220.2024.00058(332-339)Online publication date: 18-Nov-2024
  • (2023)A Lossless Compression Method for Event Cameras via Removing Spatial Redundancy2023 9th International Conference on Computer and Communications (ICCC)10.1109/ICCC59590.2023.10507631(1962-1966)Online publication date: 8-Dec-2023
  • (2023)Research on Virtual Widening of Power Information Acquisition Channel Based on LoRa and Data Compression2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)10.1109/DDCLS58216.2023.10166844(1444-1448)Online publication date: 12-May-2023
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cover image ACM Other conferences
ICDSP '19: Proceedings of the 2019 3rd International Conference on Digital Signal Processing
February 2019
170 pages
ISBN:9781450362047
DOI:10.1145/3316551
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 February 2019

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Author Tags

  1. LZ4
  2. Lempel-Ziv
  3. Lossless compression
  4. hardware architecture
  5. mobile device

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  • Research-article
  • Research
  • Refereed limited

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ICDSP 2019
ICDSP 2019: 2019 3rd International Conference on Digital Signal Processing
February 24 - 26, 2019
Jeju Island, Republic of Korea

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Cited By

View all
  • (2024)GCC: Optimizing Space Efficiency and Read Latency of SSDs with Workload-Aware Garbage Collection Aided Compression2024 IEEE 42nd International Conference on Computer Design (ICCD)10.1109/ICCD63220.2024.00058(332-339)Online publication date: 18-Nov-2024
  • (2023)A Lossless Compression Method for Event Cameras via Removing Spatial Redundancy2023 9th International Conference on Computer and Communications (ICCC)10.1109/ICCC59590.2023.10507631(1962-1966)Online publication date: 8-Dec-2023
  • (2023)Research on Virtual Widening of Power Information Acquisition Channel Based on LoRa and Data Compression2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)10.1109/DDCLS58216.2023.10166844(1444-1448)Online publication date: 12-May-2023
  • (2022)PR-SSD: Maximizing Partial Read Potential By Exploiting Compression and Channel-Level ParallelismIEEE Transactions on Computers10.1109/TC.2022.3178326(1-1)Online publication date: 2022
  • (2019)High Throughput and Low Latency LZ4 Compressor on FPGA2019 International Conference on ReConFigurable Computing and FPGAs (ReConFig)10.1109/ReConFig48160.2019.8994794(1-5)Online publication date: Dec-2019

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