The next generation of adaptive optics (AO) systems require tomographic techniques in order to correct for atmospheric turbulence along lines of sight separated from the guide stars. Multi-object adaptive optics (MOAO) is one such technique. Here we present an improved version of CARMEN, a tomographic reconstructor based on machine learning, using a dedicated neural network framework as Torch. We can observe a significant improvement on the training an execution times of the neural network, thanks to the use of the GPU.
CITATION STYLE
González-Gutiérrez, C., Santos-Rodríguez, J. D., Díaz, R. Á. F., Rolle, J. L. C., Gutiérrez, N. R., & de Cos Juez, F. J. (2017). Using GPUS to speed up a tomographic reconstructor based on machine learning. In Advances in Intelligent Systems and Computing (Vol. 527, pp. 279–289). Springer Verlag. https://doi.org/10.1007/978-3-319-47364-2_27
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