A CUDA accelerated Beam Propagation Method [BPM] Solver using the Parallel Computing Toolbox

A beam propagation method solver using the CUDA capabilities in the parallel computing toolbox.
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Updated 23 Oct 2010

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The parallel computing toolbox version 5.0 for MATLAB 2010b includes an initial capability for NVIDIA CUDA use. This entry provides a simple paraxial beam propagation method [BPM] solver that utilizes the added GPU capability. A script is also provided that runs the BPM with standard MATLAB Fourier transforms and the GPU implemented transforms. For smaller matrices, the standard MATLAB approach appears to be faster, while at larger matrices above 512x512 elements, the CUDA approach is more than twice as fast.

An effort has been made to make the program so that it will run on a computer without the parallel computing toolbox or an NVIDIA GPU. However, a comparison with standard MATLAB is only possible with those two components.

Files:

The script ScrTimeBPM.m
contains an example of how one may run the main function CUDAparaxbpm.m.
The additional files
FunPlotSim.m
FunEfieldinit.m
FunRefractIdx.m
initialize the field, update the refractive index profile, and create plots.

References:
1) www.mathworks.com/discovery/matlab-gpu.html
2) A. Weideman, Linear Dispersive Wave Equations, http://dip.sun.ac.za/~weideman/research/waves.html
3) Okamoto, K. Fundamentals of optical waveguides, Academic Press, 2000.

Cite As

Patrick Kano (2024). A CUDA accelerated Beam Propagation Method [BPM] Solver using the Parallel Computing Toolbox (https://www.mathworks.com/matlabcentral/fileexchange/29114-a-cuda-accelerated-beam-propagation-method-bpm-solver-using-the-parallel-computing-toolbox), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2010b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.1.0.0

We slightly modified the description to explain more about the functions.

1.0.0.0