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Data Structures and Transformations for Physically Based Simulation on a GPU

Perhaad Mistry, Dana Schaa, Byunghyun Jang, David Kaeli, Albert Dvornik, Dwight Meglan
Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, U.S.A.
In High Performance Computing for Computational Science – VECPAR 2010, Vol. 6449 (2011), pp. 162-171

@article{mistrydata,

   title={Data Structures and Transformations for Physically Based Simulation on a GPU},

   author={Mistry, P. and Schaa, D. and Jang, B. and Kaeli, D. and Dvornik, A. and Meglan, D.},

   booktitle={High Performance Computing for Computational Science, VECPAR 2010}

}

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As general purpose computing on Graphics Processing Units (GPGPU) matures, more complicated scientific applications are being targeted to utilize the data-level parallelism available on a GPU. Implementing physically-based simulation on data-parallel hardware requires preprocessing overhead which affects application performance. We discuss our implementation of physics-based data structures that provide significant performance improvements when used on data-parallel hardware. These data structures allow us to maintain a physics-based abstraction of the underlying data, reduce programmer effort and obtain 6x-8x speedup over previously implemented GPU kernels.
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