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Code Compression for Embedded Systems

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Abstract

Embedded systems are constrained by the available memory, and code compression techniques address this issue by reducing the code size of application programs. The main challenge for the development of an effective code compression technique is to reduce the code size without affecting the overall system performance. Code compression traditionally works on fixed-sized blocks with its efficiency limited by their small size. A new methodology, branch block, which is a series of instructions between two consecutive possible branch targets, provides larger blocks for code compression. Moreover, dictionary-based code compression schemes are the most commonly used ones, because they can provide both good compression ratio and fast decompression. In this chapter, several branch-block based methods, as well as new dictionary-based code compression methods are presented. These methods can achieve a good compression ratio (CR) (the compressed code size divided by original code size), with little or no hardware overheads.

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Author information

Authors and Affiliations

  1. National Taiwan University of Science and Technology, Taipei City, Taiwan

    Chang Hong Lin, Wei-Jhih Wang, Jui-Chun Chen & Che-Wei Lin

Authors
  1. Chang Hong Lin
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  2. Wei-Jhih Wang
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  3. Jui-Chun Chen
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  4. Che-Wei Lin
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Correspondence to Chang Hong Lin .

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Editors and Affiliations

  1. Dept. of ECE and UMIACS, University of Maryland, College Park, MD, USA

    Shuvra S. Bhattacharyya

  2. Dept. of Computer Science, University of California, Los Angeles, CA, USA

    Miodrag Potkonjak

  3. Dept. of EECS, Syracuse University, Syracuse, NY, USA

    Senem Velipasalar

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Lin, C.H., Wang, WJ., Chen, JC., Lin, CW. (2020). Code Compression for Embedded Systems. In: Bhattacharyya, S., Potkonjak, M., Velipasalar, S. (eds) Embedded, Cyber-Physical, and IoT Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-16949-7_6

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  • DOI: https://doi.org/10.1007/978-3-030-16949-7_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-16948-0

  • Online ISBN: 978-3-030-16949-7

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