3758

GPU-based simulation of cellular neural networks for image processing

R. Dolan, G. DeSouza
Vision-Guided and Intelligent Robotics Laboratory, University of Missouri, Columbia, MO USA
International Joint Conference on Neural Networks, 2009. IJCNN 2009

@article{dolan2009gpu,

   title={GPU-based simulation of cellular neural networks for image processing},

   author={Dolan, R. and DeSouza, G.},

   year={2009},

   publisher={IEEE}

}

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The inherent massive parallelism of cellular neural networks makes them an ideal computational platform for kernel-based algorithms and image processing. General-purpose GPUs provide similar massive parallelism, but it can be difficult to design algorithms to make optimal use of the hardware. The presented research includes a GPU abstraction based on cellular neural networks. The abstraction offers a simplified view of massively parallel computation which remains reasonably efficient. An image processing library with visualization software has been developed to showcase the flexibility and power of cellular computation on GPUs. Benchmarks of the library indicate that commodity GPUs can be used to significantly accelerate CNN research and offer a viable alternative to CPU-based image processing algorithms.
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