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Comparing CUDA and OpenGL implementations for a Jacobi iteration

Ronan Amorim, Gundolf Haase, Manfred Liebmann, Rodrigo Weber dos Santos
Institute for Math. & Sci. Comput., Karl Franzens University of Graz, Graz, Austria
International Conference on High Performance Computing & Simulation, 2009. HPCS ’09, p.22-32

@conference{amorim2009comparing,

   title={Comparing CUDA and OpenGL implementations for a Jacobi iteration},

   author={Amorim, R. and Haase, G. and Liebmann, M. and Weber dos Santos, R.},

   booktitle={High Performance Computing & Simulation, 2009. HPCS’09. International Conference on},

   pages={22–32},

   year={2009},

   organization={IEEE}

}

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The use of the GPU as a general purpose processor is becoming more popular and there are different approaches for this kind of programming. In this paper we present a comparison between different implementations of the OpenGL and CUDA approaches for solving our test case, a weighted Jacobi iteration with a structured matrix originating from a finite element discretization of the elliptic PDE part of the cardiac bidomain equations. The CUDA approach using textures showed to be the fastest with a speedup of 31 over a CPU implementation using one core and SSE. CUDA showed to be an efficient and easy way of programming GPU for general purpose problems, though it is also easier to write inefficient codes.
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