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GPU Accelerated Numerical Solutions to Chaotic PDEs

J.R. Seaton, J.C Sprott
Department of Physics, University of Wisconsin – Madison, 1150 University Avenue, Madison, Wisconsin 53706
University of Wisconsin – Madison, 2011

@article{seatona2011gpu,

   title={GPU Accelerated Numerical Solutions to Chaotic PDEs},

   author={Seatona, JR and Sprotta, JC},

   year={2011}

}

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In this study, chaotic partial differential equations (PDEs) were numerically solved using a parallel algorithm on graphics processing units (GPU). This new method will aid in our search for simple examples of chaotic PDEs. Computational time using the GPU was compared to other languages such as Matlab and PowerBASIC. The GPU algorithm was optimized using shared memory and a data padding method was analyzed. We report that we have simulated selected chaotic PDE candidates with greater spatial resolution and speed using the GPU.
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