JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2018, Vol. 48 ›› Issue (3): 110-114.doi: 10.6040/j.issn.1672-3961.0.2017.413

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Parallelization and GPU acceleration of compressive sensing reconstruction algorithm

HE Wenjie1, HE Weichao2, SUN Quansen1*   

  1. 1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China;
    2. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, China
  • Received:2017-05-09 Online:2018-06-20 Published:2017-05-09

Abstract: Aimed at the poor real-time performance of the compression sensing reconstruction algorithm, the parallel acceleration of the compressive sampling matching pursuit(CoSaMP)algorithm was proposed. Coarse grained parallelization of reconstruction algorithm was realized based on multithreading technology. The hotspot of CoSaMP algorithm was analyzed, and the matrix operation which was time-consuming was transplanted to graphics processing unit(GPU)to achieve fine grained parallelization of the algorithm. The experiments on the test image showed that 50-fold acceleration speedup was achieved and the study reduced the computing time cost of the reconstruction algorithm effectively.

Key words: reconstruction, algorithm acceleration, graphics processing unit, compressed sensing, parallelization computing

CLC Number: 

  • TP391
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