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Solving diffractive optics problems using graphics processing units

D. L. Golovashkin, N. L. Kasanskiy
Image Processing Systems Institute of the RAS, Samara, Russia and Samara State Aerospace University, Samara, Russia
Optical Memory and Neural Networks, Volume 20 Issue 2, 2011

@article{golovashkin2011solving,

   title={Solving diffractive optics problems using graphics processing units},

   author={Golovashkin, DL and Kasanskiy, NL},

   journal={Optical Memory & Neural Networks},

   volume={20},

   number={2},

   pages={85–89},

   year={2011},

   publisher={Springer}

}

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Techniques for applying graphics processing units (GPU) to the general-purpose nongraphics computations proposed in recent years by the companies ATI (AMD FireStream, 2006) and NVIDIA (CUDA: Compute Unified Device Architecture, 2007) have given an impetus to developing algorithms and software packages for solving problems of diffractive optics with the aid of the GPU. The computations based on the wide-spread Ray Tracing method were among the first to be implemented using the GPU. The method attracted the attention of the CUDA technology architects, who proposed its GPU-based implementation at the conference NVISION08 (2008). The potential of this direction is associated both with the research into the general issues of mapping of the Ray Tracing method onto the GPU architecture (involving the use of various grid domains and trees) and with developing dedicated software packages (RTE and Linzik projects). In this work, a special attention is given to the overview of techniques for the GPU-aided implementation of the FDTD (finite-difference time-domain) method, which offers an instrument for solving problems of micro- and nanooptics using the rigorous electromagnetic theory. The review of the related papers ranges from the initial research (based on the use of textures) to the complete software solutions (like FDTD Software and FastFDTD).
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