Parallel algorithms for conjugate gradient method of adaptive optics

Lei Song; Xingming Chen; Jun Dai; Longfeng Zhou; Jun Chen

doi:10.1117/12.2564662

17 April 2020 Parallel algorithms for conjugate gradient method of adaptive optics

Lei Song, Xingming Chen, Jun Dai, Longfeng Zhou, Jun Chen

Proceedings Volume 11455, Sixth Symposium on Novel Optoelectronic Detection Technology and Applications; 114553J (2020) https://doi.org/10.1117/12.2564662
Event: Sixth Symposium on Novel Photoelectronic Detection Technology and Application, 2019, Beijing, China

Abstract

In the wavefront reconstruction process of adaptive optics, the conventional CPU wavefront reconstruction algorithm cannot meet the real-time requirements of the system. In order to ensure that the calculation time meets the closed-loop control requirements, this paper proposes a GPU-based iterative algorithm using conjugate gradient of wavefront, which is the wavefront reconstruction algorithm of CUDA architecture.By simulation using the GPU NVIDIA GeForce GTX 1070, the experimental results of adaptive optics systems with different cell numbers show that the GPU has a significant improvement on the wavefront reconstruction algorithm. When the number of elements of restoration matrix reaches 5121*5121, the algorithm improves the running speed by 76.6 times compared with the CPU algorithm, which provides a better option subsequent adaptive wavefront reconstruction.

Citation Download Citation

Lei Song, Xingming Chen, Jun Dai, Longfeng Zhou, and Jun Chen "Parallel algorithms for conjugate gradient method of adaptive optics", Proc. SPIE 11455, Sixth Symposium on Novel Optoelectronic Detection Technology and Applications, 114553J (17 April 2020); https://doi.org/10.1117/12.2564662

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