Data layout pruning on GPU

Applied Mathematics and Information Sciences

Volumn 5, Issue SUPPL.2, 2011, Pages

  Gan, Xinbiao ^a   Wang, Zhiying ^a   Shen, Li ^a   Zhu, Qi ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

Data layout pruning; GPU; Memory optimization

Indexed keywords

EID: 84863119328     PISSN: 19350090     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (13)

1. J. Nickolls, William J. Dally. The GPU Computing era. IEEE Micro, 2010:31(2), pp. 1-10.
2. S. Ryoo, C. I. Rodrigues, S. S. Baghsorkhi, et al. Optimization principles and application performance evaluation of a multithreaded gpu using cuda. In PPoPP, pp. 73-82, 2008.
3. S. Hong, H. Kim. An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness. In ISCA, pp. 152-163, 2009.
4. J. Siegel, J. Ributzka, X.M. Li. CUDA Memory Optimizations for Large Data-Structures in the Gravit Simulator. Proceedings of the International Conference on Parallel Processing Workshops, pp.174-181, 2009.
5. I-Jui Sung, Wen-Mei Hwu. Data Layout Transformation for Structured-Grid Codes on GPU. Proceedings of the Workshop on Language, Compiler, and Architecture Support for GPGPU, pp.85-94, 2010.
6. NVIDIA Corporation. CUDA Programming Guide 2.0, July 2008.
7. IMPACT Research Group. Parboil benchmark suite. http://impact.crhc.illinois.edu/parboil.php.
8. J. E. Stone, J. C. Phillips, P. L. Freddolino, et al. Accelerating molecular modeling applications with graphics processors. Journal of Computational Chemistry, 2007:28(16), pp. 2618 - 2640.
9. S. S. Stone, H. Yi, J. P. Haldar, et al. How GPUs Can Improve the Quality of Magnetic Resonance Imaging. Proceedings of the 5th International Conference on Computing Frontiers, pp. 1-9, 2008.
10. S. S. Stone, J. P. Haldar, S. C. Tsao, et al. Accelerating Advanced MRI Reconstructions on GPUs. Proceedings of the Sixth International Conference on Computing Frontiers, pp. 1283-1286, 2009.
11. J. Rys, M. Dupuis, H. F. King. Computation of Electron Repulsion Integrals Using the Rys Quadrature Method. Journal of Computational Chemistry, 1983:4(2), pp. 154-157.
12. M. Dupuis and A. Marquez. The Rys Quadrature revisited: A novel formulation for the efficient computation of electron repulsion integrals over Gaussian functions. Journal of Chemical Physics, 2001:114(5), pp.2067-2078.
13. V. V. Kindratenko, A. D. Myers, R. J. Brunner. Implementations of the two-point angular correlation function on a high-performance reconfigurable computer. Journal of Scientific Programming, 2009:17(3), pp. 247-259.