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Proceedings Paper

Linear Bregman algorithm implemented in parallel GPU
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Paper Abstract

At present, most compressed sensing (CS) algorithms have poor converging speed, thus are difficult to run on PC. To deal with this issue, we use a parallel GPU, to implement a broadly used compressed sensing algorithm, the Linear Bregman algorithm. Linear iterative Bregman algorithm is a reconstruction algorithm proposed by Osher and Cai. Compared with other CS reconstruction algorithms, the linear Bregman algorithm only involves the vector and matrix multiplication and thresholding operation, and is simpler and more efficient for programming. We use C as a development language and adopt CUDA (Compute Unified Device Architecture) as parallel computing architectures. In this paper, we compared the parallel Bregman algorithm with traditional CPU realized Bregaman algorithm. In addition, we also compared the parallel Bregman algorithm with other CS reconstruction algorithms, such as OMP and TwIST algorithms. Compared with these two algorithms, the result of this paper shows that, the parallel Bregman algorithm needs shorter time, and thus is more convenient for real-time object reconstruction, which is important to people’s fast growing demand to information technology.

Paper Details

Date Published: 5 August 2015
PDF: 8 pages
Proc. SPIE 9622, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 962216 (5 August 2015); doi: 10.1117/12.2193282
Show Author Affiliations
Pengyan Li, Beijing Institute of Technology (China)
Jue Ke, Beijing Institute of Technology (China)
Dong Sui, Beijing Institute of Technology (China)
Ping Wei, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 9622:
2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology
Guangming Shi; Xuelong Li; Bormin Huang, Editor(s)

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