Laser & Optoelectronics Progress, Volume. 56, Issue 7, 070101(2019)

GPU Acceleration in Wave-Front Sensorless Adaptive Wave-Front Correction System

Xizheng Ke, Yunfeng Zhang*, Ying Zhang, and Sichen Lei
Author Affiliations
  • School of Automation and Information Engineering, Xi'an University of Technology, Xi'an, Shaanxi 710048, China
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    As for the wave-front sensorless adaptive wave-front correction system based on the stochastic parallel gradient descent (SPGD) algorithm, its convergence speed is too slow to satisfy the real-time requirement of a wireless optical coherent communication system. The parallel processing base on the SPGD algorithm is introduced and the graphics processing unit (GPU) parallel computing is used to improve the convergence speed of the correction system. The average gray value of the surrounding 400 pixels centered on the centroid of the real-time spot detected by CCD camera is employed as the value of system performance index. GPU multithreading operation is used to accelerate the solving process of the performance index and the updating process of the deformable mirror control voltage vector. The results from the indoor experiments and the external coherent light experiments show that the Strehl ratio is larger than 0.8 and the maximum time acceleration ratio is up to 8.6. Moreover, the convergence speed of the GPU accelerated wave-front correction system is improved and simultaneously the correction effect is ensured.

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    Xizheng Ke, Yunfeng Zhang, Ying Zhang, Sichen Lei. GPU Acceleration in Wave-Front Sensorless Adaptive Wave-Front Correction System[J]. Laser & Optoelectronics Progress, 2019, 56(7): 070101

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    Paper Information

    Category: Atmospheric Optics and Oceanic Optics

    Received: Sep. 29, 2018

    Accepted: Oct. 24, 2018

    Published Online: Jul. 30, 2019

    The Author Email: Zhang Yunfeng (1195970257@qq.com)

    DOI:10.3788/LOP56.070101

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