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GPGPU-Aided 3D Staggered-grid Finite-difference Seismic Wave Modeling

Chang Cai, Haiqing Chen, Ze Deng, Dan Chen, Samee U. Khan, Ke Zeng, Minxiao Wu
School of Computer Science, China University of Geosciences, Wuhan, China
12th International Conference on Scalable Computing and Communications (ScalCom), 2012

@article{cai2012gpgpu,

   title={GPGPU-Aided 3D Staggered-grid Finite-difference Seismic Wave Modeling},

   author={Cai, C. and Chen, H. and Deng, Z. and Chen, D. and Khan, S.U. and Zeng, K. and Wu, M.},

   year={2012}

}

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Finite difference is a simple, fast and effective numerical method for seismic wave modeling, and has been widely used in forward waveform inversion and reverse time migration. However, intensive calculation of three-dimensional seismic forward modeling has been restricting the industrial application of 3D pre-stack reverse time migration and inversion. Aiming at this problem, in this paper, a parallelized 3D Staggered-grid Finite-difference has been developed using General-purpose computing on the graphics processing unit (GPGPU), namely G-3DFD, since the emergence of graphic processing units (GPU) as an effective alternative to traditional general purpose processors has become increasingly capable in accelerating large-scale scientific computing. We analyze three-dimensional staggered grid finite difference method for the implementation on GPU, making possible the industrial application of 3D pre-stack reverse time migration and inversion. Experiments show that G-3DFD has dramatically improved the runtime performance 88 times on modern GPGPU platforms comparing to the original CPU implementation methods.
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