Data Structures and Transformations for Physically Based Simulation on a GPU
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}
}
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.
February 22, 2011 by hgpu
