Volume 44 Issue 1
Feb.  2024
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Article Navigation >  Chinese Journal of Space Science  > 2024  >  44(1): 95-102 Open Access
TAN Pengyuan, XUE Changbin, ZHOU Li. Acceleration of Remote Sensing Image Filtering Based on Embedded CPU+GPU Heterogeneous Platform (in Chinese). Chinese Journal of Space Science, 2024, 44(1): 95-102 doi: 10.11728/cjss2024.01.2023-0033
Citation: TAN Pengyuan, XUE Changbin, ZHOU Li. Acceleration of Remote Sensing Image Filtering Based on Embedded CPU+GPU Heterogeneous Platform (in Chinese). Chinese Journal of Space Science, 2024, 44(1): 95-102 doi: 10.11728/cjss2024.01.2023-0033
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Acceleration of Remote Sensing Image Filtering Based on Embedded CPU+GPU Heterogeneous Platform

doi: 10.11728/cjss2024.01.2023-0033 cstr: 32142.14.cjss2024.01.2023-0033
  • 1.

    National Space Science Center, Chinese Academy of Sciences, Beijing 100190

  • 2.

    University of Chinese Academy of Sciences, Beijing 100049

  • Received Date: 2023-03-02
  • Rev Recd Date: 2023-04-26
    • Available Online: 2023-07-27
    Abstract
  • A method is proposed for accelerating remote sensing image filtering in real-time using an embedded CPU + GPU heterogeneous platform for satellite-based image processing. the algorithm was initially parallelized through data division and mapping, leveraging the parallel computing capabilities of the GPU. Subsequently, hardware resources like the vector unit and cache of the GPU were employed to enhance algorithm speed through vectorization, vector permutation, and workgroup tuning. The feasibility and efficiency of this accelerated design were validated on an embedded development board. The experiments demonstrate a speedup ranging from 4.08 to 16.92 times when incorporating GPU parallel processing, compared to the serial implementation on a single CPU. Further optimization using GPU hardware resources can push the speedup to 15.38 to 56.41 times.

     

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