2011-03-14
GPU Approach for Hertzian Potential Formulation Tool Oriented on Electromagnetic Nanodevices
By
Progress In Electromagnetics Research M, Vol. 17, 135-150, 2011
Abstract
The time domain modeling and simulation of electromagnetic (EM) waves interaction with nanodevices, at high spatial and time resolution, requires high computational power. For the first time, in this paper we present an effective implementation of the Hertzian Potential Formulation (HPF) on the Graphics Processing Units (GPUs), through the NVIDIA's CUDA (Compute Unified Device Architecture) programming model. It accelerates the nanodevice EM simulations at nanometer scale harnessing the massive parallelism of the GPU based systems. This study is useful for similar electromagnetic codes including the Finite Difference approaches. The results demonstrate that this GPU tool outperforms the CPU based HPF implementation, reaching a speedup from 30× to 70×.
Citation
Daniele Tartarini, and Alessandro Massaro, "GPU Approach for Hertzian Potential Formulation Tool Oriented on Electromagnetic Nanodevices," Progress In Electromagnetics Research M, Vol. 17, 135-150, 2011.
doi:10.2528/PIERM11020309
References

1. Massaro, A., M. Grande, R. Cingolani, A. Passaseo, and M. De Vittorio, "Design and modelling of tapered waveguide for photonic crystal slab coupling by using time-domain Hertzian potential formulation," Opt. Express, Vol. 15, No. 25, 16484-16499, 2007.
doi:10.1364/OE.15.016484        Google Scholar

2. VanRoey, J., J. van Derdonk, and P. Lagasse, "Beam-propagation method: Analysis and assessment," J. Opt. Soc. Am., Vol. 71, 803-810, 1981.
doi:10.1364/JOSA.71.000803        Google Scholar

3. Yee, K. S., "Numerical solution of initial boundary value problems involving Maxwell's equations in isotropic media," IEEE Trans. Antennas Propagation, Vol. 14, No. 8, 302-307, 1966.        Google Scholar

4. Massaro, A. and T. Rozzi, "Rigorous time-domain analysis of dielectric optical waveguides using Hertzian potentials formulation," Opt. Express, Vol. 14, No. 5, 2027-2036, 2006.
doi:10.1364/OE.14.002027        Google Scholar

5. Massaro, A., V. Tasco, M. T. Todaro, R. Cingolani, M. De Vittorio, and A. Passaseo, "Scalar time domain modeling and coupling of second harmonic generation process in gaas discontinuous optical waveguides," Opt. Express, Vol. 16, No. 19, 14496-14510, 2008.
doi:10.1364/OE.16.014496        Google Scholar

6. Owens, J. D., M. Houston, et al. "GPU computing," Proceedings of the IEEE, Vol. 96, No. 5, 879-899, May 2008.
doi:10.1109/JPROC.2008.917757        Google Scholar

7. Nickolls, J. and W. J. Dally, "The GPU computing era," IEEE Micro., Vol. 30, 56-69, 2010.
doi:10.1109/MM.2010.41        Google Scholar

8. Huang, S., S. Xiao, and W. Feng, "On the energy efficiency of graphics processing units for scientific computing," IEEE International Symposium on Parallel & Distributed Processing, 1-8, 2009.
doi:10.1109/IPDPS.2009.5160980        Google Scholar

9. Krakiwsky, S. E., L. E. Turner, and M. M. Okoniewski, "Acceleration of finite-difference time-domain (FDTD) using graphics processor units (GPU)," IEEE MTT-S Int. Microwave Symp. Digest, 1033-1036, 2004.        Google Scholar

10. Peng, S. X. and Z. P. Nie, "Acceleration of the method of moments calculations by using graphics processing units," IEEE Trans. Antennas and Propagation, Vol. 56, No. 7, 2130-2133, Jul. 2008.
doi:10.1109/TAP.2008.924768        Google Scholar

11. Zainud-Deen, S. H., E. El-Deen, M. S. Ibrahim, K. H. Awadalla, and A. Z. Botros, "Electromagnetic scattering using gpu-based ¯nite di®erence frequency domain method," Progress In Electromagnetics Research B, Vol. 16, 351-369, 2009.
doi:10.2528/PIERB09060703        Google Scholar

12. Jiang, , W. Q., M. Zhang, and Y. Wang, "CUDA-based radiative transfer method with application to the EM scattering from a twolayer canopy model," Journal of Electromagnetic Waves and Applications, Vol. 24, No. 17-18, 2509-2521, 2010.
doi:10.1163/156939310793675772        Google Scholar

13. Xu, K., Z. H. Fan, D. Z. Ding, and R. S. Chen, "GPU accelerated unconditionally stable Crank-Nicolson FDTD method for the analysis of three-dimensional microwave circuits," Progress In Electromagnetics Research, Vol. 102, 381-395, 2010.
doi:10.2528/PIER10020606        Google Scholar

14. Mur, G., "Absorbing boundary conditions for the finite-difference approximation of the time-domain electromagnetic field equations," IEEE Trans. Electromagn. Compat., Vol. 23, 377-382, 1981.
doi:10.1109/TEMC.1981.303970        Google Scholar

15. Taflove, A. and S. C. Hagness, Computational Electrody-namic: The Finite-difference Time-domain Method, 2nd Ed., Chaps. 2, 4, and 7, Arthec House Publishers, London, 2000.

16. Lindholm, E, J. Nickolls, S. Oberman, and J. Montrym, "NVIDIA Tesla: A unified graphics and computing architecture," IEEE Micro., Vol. 28, 39-55, 2008.
doi:10.1109/MM.2008.31        Google Scholar

., NVIDIA CUDA C Programming guide v.3.2. Nvidia Corp., 2010.        Google Scholar

18., NVIDIA CUDA C Best Practices guide v.3.2. Nvidia Corp., 2010.        Google Scholar

19. Patterson, D. A. and J. L. Hennessy, "Computer Organization and Design: The Hardware/Software Interface," Morgan Kaufmann, 2008.        Google Scholar

20. Kirk, D. B. and W.-M. W. Hwu, Programming Massively Parallel Processors: A Hands-on Approach, Morgan Kaufmann, 2010.

21. Ryoo , S., C. I. Rodrigues, S. S. Baghsorkhi, S. S. Stone, D. B. Kirk, and W.-M. W. Hwu, "Optimization principles and application performance evaluation of a multithreaded GPU using CUDA," Proceedings of the 13th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, ACM, 73-82, New York, USA, 2008.        Google Scholar

22. Courant, R., K. Friedrichs, and H. Lewy, "On the partial difference equations of mathematical physics," IBM Journal of Research and Development, Vol. 11, No. 2, 215-234, 1967.
doi:10.1147/rd.112.0215        Google Scholar