Compute Unified Device Architecture (CUDA) Based Finite- Difference Time-Domain (FDTD) Implementation
Keywords:
Compute Unified Device Architecture (CUDA) Based Finite- Difference Time-Domain (FDTD) ImplementationAbstract
Recent developments in the design of graphics processing units (GPUs) have made it possible to use these devices as alternatives to central processor units (CPUs) and perform high performance scientific computing on them. Though several implementations of finitedifference time-domain (FDTD) method have been reported, the unavailability of high level languages to program graphics cards had been a major obstacle for scientists and engineers who would want to develop codes for graphics cards. Relatively recently, compute unified device architecture (CUDA) development environment has been introduced by NVIDIA and made GPU computing much easier. This paper presents an implementation of FDTD method based on CUDA. Two thread-to-cell mapping algorithms are presented. The details of the implementation are provided and strategies to improve the performance of the FDTD simulations are discussed.
Downloads
References
K. S. Yee, “Numerical Solution of Inital
Boundary Value Problems Involving
Maxwell's Equations in Isotropic Media,”
IEEE Transactions on Antennas and
Propagation, vol. 14, pp. 302–307, May
A. Taflove and S. C. Hagness, Computational
Electrodynamics: The Finite-Difference
Time-Domain Method, 3rd edition, Artech
House, 2005.
A. Elsherbeni and V . Demir, “The Finite
Difference Time Domain Method for
Electromagnetics: With MATLAB
Simulations,” SciTech Publishing, 2009.
S. E. Krakiwsky, L. E. Turner, and M. M.
Okoniewski, “Graphics Processor Unit (GPU)
Acceleration of Finite-Difference Time-
Domain (FDTD) Algorithm,” Proc. 2004
International Symposium on Circuits and
Systems, vol. 5, pp. V-265–V-268, May 2004.
S. E. Krakiwsky, L. E. Turner, and M. M.
Okoniewski, “Acceleration of Finite-
Difference Time-Domain (FDTD) Using
Graphics Processor Units (GPU),” 2004 IEEE
MTT-S International Microwave Symposium
Digest, vol. 2, pp. 1033–1036, June 2004.
R. Schneider, S. Krakiwsky, L. Turner, and
M. Okoniewski, “Advances in Hardware
Acceleration for FDTD,” Ch. 20 in
Computational Electrodynamics: The Finite-
Difference Time-Domain Method, 3rd
edition, Artech House, 2005.
M. J. Inman, A. Z. Elsherbeni, and C. E.
Smith “GPU Programming for FDTD
Calculations,” The Applied Computational
Electromagnetics Society (ACES) Conference,
M. J. Inman and A. Z. Elsherbeni,
“Programming Video Cards for
Computational Electromagnetics
Applications,” IEEE Antennas and
Propagation Magazine, vol. 47, no. 6, pp. 71–
, Dec. 2005.
M. J. Inman and A. Z. Elsherbeni,
“Acceleration of Field Computations Using
Graphical Processing Units,” The Twelfth
Biennial IEEE Conference on
Electromagnetic Field Computation CEFC
, April 30 - May 3, 2006.
M. J. Inman, A. Z. Elsherbeni, J. G. Maloney,
and B. N. Baker, “Practical Implementation of
a CPML Absorbing Boundary for GPU
Accelerated FDTD Technique,” The 23rd
Annual Review of Progress in Applied
Computational Electromagnetics Society, 19-
March 2007.
S. Adams, J. Payne, and R. Boppana, “Finite
Difference Time Domain (FDTD)
Simulations Using Graphics Processors,”
Proceedings of the 2007 DoD High
Performance Computing Modernization
Program Users Group (HPCMP) Conference,
pp. 334–338, 2007.
D. K. Price, J. R. Humphrey, and E. J.
Kelmelis, “GPU-based Accelerated 2D and
D FDTD Solvers,” in Physics and
Simulation of Optoelectronic Devices XV, of
Proceedings of SPIE, vol. 6468, Jan. 2007.
D. K. Price, J. R. Humphrey, and E. J.
Kelmelis, “Accelerated Simulators for Nano-
Photonic Devices,” International Conference
on Numerical Simulation of Optoelectronic
Devices 2007, pp. 103–104, Sept. 2007.
M. Inman, A. Elsherbeni, J. Maloney, and B.
Baker, “Practical Implementation of a CPML
Absorbing Boundary for GPU Accelerated
FDTD Technique,” Applied Computational
Electromagnetics Society Journal, vol. 23, no.
, pp. 16–22, 2008.
M. J. Inman and A. Z. Elsherbeni,
“Optimization and parameter exploration
using GPU based FDTD solvers,” IEEE MTT-
S International Microwave Symposium
Digest, pp. 149-152, June 2008.
ACES JOURNAL, VOL. 25, NO. 4, APRIL 2010
N. Takada, N. Masuda, T. Tanaka, Y. Abe,
and T. Ito, “A GPU Implementation of the 2-
D Finite-Difference Time-Domain Code
Using High Level Shader Language,” Applied
Computational Electromagnetics Society
Journal, vol. 23, no. 4, pp. 309–316, 2008.
A. Valcarce, G. de la Roche, and J. Zhang, “A
GPU Approach to FDTD for Radio Coverage
Prediction,” Proceedings of the 11th IEEE
Singapore International Conference on
Communication Systems (ICCS '08), pp.
–1590, Nov. 2008.
P. Sypek and M. Michal, “Optimization of a
FDTD Code for Graphical Processing Units,”
th International Conference on Microwaves,
Radar and Wireless Communications
(MIKON), pp. 1–3, May 2008.
A. Balevic, L. Rockstroh, A. Tausendfreund,
S. Patzelt, G. Goch, and S. Simon,
“Accelerating Simulations of Light Scattering
Based on Finite-Difference Time-Domain
Method with General Purpose GPUs,”
Proceedings of the 2008 11 th IEEE
International Conference on Computational
Science and Engineering, pp. 327–334, 2008.
P. Sypek, A. Dziekonski, and M. Mrozowski,
“How to Render FDTD Computations More
Effective Using a Graphics Accelerator,”
IEEE Transactions on Magnetics, vol. 45, no.
, pp. 1324–1327, 2009.
N. Takada, T. Shimobaba, N. Masuda, and T.
Ito, “High-speed FDTD Simulation Algorithm
for GPU with Compute Unified Device
Architecture,” IEEE International Symposium
on Antennas & Propagation & USNC/URSI
National Radio Science Meeting,. 4, 2009.
A. Valcarce, G. De La Roche, A. Jüttner, D.
López-Pérez, and J. Zhang, “Applying FDTD
to the coverage prediction of WiMAX
femtocells,” EURASIP Journal on Wireless
Communications and Networking, Feb. 2009.
C. Ong, M. Weldon, D. Cyca, and M.
Okoniewski, “Acceleration of Large-Scale
FDTD Simulations on High Performance
GPU Clusters,” 2009 IEEE International
Symposium on Antennas & Propagation &
USNC/URSI National Radio Science Meeting,
M. J. Inman, A. Elsherbeni, and V . Demir,
“Graphics Processing Unit Acceleration of
Finite Difference Time Domain”, Ch. 12 in
The Finite Difference Time Domain Method
for Electromagnetics (with MATLAB
Simulations), SciTech Publishing, 2009.
I. Buck, Brook Spec v0.2, Stanford Univ.
Press, 2003.
NVIDIA CUDA ZONE,
http://www.nvidia.com/object/cuda_home.ht
ml.
CUDA 2.1 Quickstart Guide,
http://www.nvidia.com/object/cuda_develop.
html.
J. A. Roden and S. Gedney, “Convolution
PML (CPML): An Efficient FDTD
Implementation of the CFS-PML for
Arbitrary Media,” Microwave and Optical
Technology Letters, vol. 27, no. 5, pp. 334–
, 2000.
CUDA 2.1 Programming Guide,
http://www.nvidia.com/object/cuda_develop.
html.
CUDA Best Practices Guide,
http://www.nvidia.com/object/cuda_develop.
html.
