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Space Compression Algorithms Acceleration on Embedded Multi-core and GPU Platforms

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Published:19 December 2022Publication History
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Abstract

Future space missions will require increased on-board computing power to process and compress massive amounts of data. Consequently, embedded multi-core and GPU platforms are considered, which have been shown beneficial for data processing. However, the acceleration of data compression - an inherently sequential task - has not been explored. In this on-going research paper, we parallelize two space compression standards on both CPUs and GPUs using two candidate embedded GPU platforms for space showing that despite the challenging nature of CCSDS algorithms, their parallelization is possible and can provide significant performance benefits.

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  • Published in

    cover image ACM SIGAda Ada Letters
    ACM SIGAda Ada Letters  Volume 42, Issue 1
    June 2022
    67 pages
    ISSN:1094-3641
    DOI:10.1145/3577949
    Issue’s Table of Contents

    Copyright © 2022 Copyright is held by the owner/author(s)

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    Association for Computing Machinery

    New York, NY, United States

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    • Published: 19 December 2022

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