CUDA-MPI-FDTD implementation of Maxwell's equations in general dispersive media

Zunoubi, Mohammad R.; Payne, Jerry A.; Roach, William P.

doi:10.1117/12.918429

Cited by 10 publications

(11 citation statements)

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“…We also need to note that in these simulations, minimum data transfer between the device and the host was required. However, the above speedup factors could be reduced drastically for applications involving large amount of data transfer as discussed in [12].…”

Section: Resultsmentioning

confidence: 99%

Analysis of 3-Dimensional Electromagnetic Fields in Dispersive Media Using Cuda

Zunoubi

Payne²

2011

PIER M

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Abstract-This research presents the implementation of the FiniteDifference Time-Domain (FDTD) method for the solution of 3-dimensional electromagnetic problems in dispersive media using Graphics Processor Units (GPUs). By using the newly introduced CUDA technology, we illustrate the efficacy of GPUs in accelerating the FDTD computations by achieving appreciable speedup factors with great ease and at no extra hardware/software cost. We validate our approach by comparing the results with their corresponding simulated results obtained from Remcom's XFDTD software.

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Section: Resultsmentioning

confidence: 99%

Analysis of 3-Dimensional Electromagnetic Fields in Dispersive Media Using Cuda

Zunoubi

Payne²

2011

PIER M

Self Cite

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“…In order to model them accurately, different dispersive models have been incorporated into Maxwell equations [13,[16][17][18][19][20][21][22][23][24][25][26][27][28]. Most of the available dispersive models are in frequency domain, so as to make them consistent with time domain methods different approaches such as recursive convolution (RC), piecewise linear recursive convolution (PLRC), z-transform and auxiliary differential equation (ADE) [13,18,[24][25][26] are used.…”

Section: Formulationsmentioning

confidence: 99%

“…Since then, GPU-accelerated FDTD method has been applied to different applications. In [16], the two-dimensional FDTD method is implemented on GPU for dispersive media using single pole Debye model with piecewise linear recursive convolution (PLRC) method for microwave applications. In [17], the threedimensional FDTD method is implemented on GPU for low and mid frequency acoustics applications.…”

Section: Introductionmentioning

confidence: 99%

Implementation of the FDTD Method Based on Lorentz-Drude Dispersive Model on Gpu for Plasmonics Applications

Lee¹,

Ahmed²,

Goh³

et al. 2011

PIER

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Abstract-We present a three-dimensional finite difference time domain (FDTD) method on graphics processing unit (GPU) for plasmonics applications. For the simulation of plasmonics devices, the Lorentz-Drude (LD) dispersive model is incorporated into Maxwell equations, while the auxiliary differential equation (ADE) technique is applied to the LD model. Our numerical experiments based on typical domain sizes as well as plasmonics environment demonstrate that our implementation of the FDTD method on GPU offers significant speed up as compared to the traditional CPU implementations.

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“…Among different approaches, such as using clusters [22] or field programmable gate arrays (FPGA) [23], using graphics processing unit (GPU) is more efficient, and cheaper in reducing runtimes. In spite of large efforts on GPU parallel programming for ordinary FDTD [24][25][26][27][28][29][30][31], GPU parallel programming for SF-FDTD has not been reported yet, to the best of our knowledge. Even though cluster programming by using Massage Passing Interface (MPI) has been reported for SF-FDTD [32,33], it has not achieved good efficiency, compared to the GPU implementation reported here.…”

Section: Introductionmentioning

confidence: 99%

Gpu Implementation of Split-Field Finite-Difference Time-Domain Method for Drude-Lorentz Dispersive Media

Shahmansouri¹,

Rashidian²

2012

PIER

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Abstract-Split-field finite-difference time-domain (SF-FDTD) method can overcome the limitation of ordinary FDTD in analyzing periodic structures under oblique incidence. On the other hand, huge run times of 3D SF-FDTD, is practically a major burden in its usage for analysis and design of nanostructures, particularly when having dispersive media. Here, details of parallel implementation of 3D SF-FDTD method for dispersive media, combined with totalfield/scattered-field (TF/SF) method for injecting oblique plane wave, are discussed. Graphics processing unit (GPU) has been used for this purpose, and very large speed up factors have been achieved. Also a previously reported formulation of SF-FDTD based on the Drude model for dispersive media, is extended to cover Drude-Lorentz model, which is usually needed for materials such as gold. The resulting reduction in the number of variables in this formulation, not only helps in reducing the computational time, but also makes it possible to be implemented in GPU, where its memory limitation is a major concern. As an example for demonstrating the importance of this method in optimization of nanophotonics structures, improvement in the performance of a refractive index sensor, made of an array of nanodisks, using suitable angle of incidence is reported. To the best of our knowledge this is the first report of GPU implementation of SF-FDTD method, capable of analyzing periodic dispersive media under oblique incidence.

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CUDA-MPI-FDTD implementation of Maxwell's equations in general dispersive media

Cited by 10 publications

References 0 publications

Analysis of 3-Dimensional Electromagnetic Fields in Dispersive Media Using Cuda

Analysis of 3-Dimensional Electromagnetic Fields in Dispersive Media Using Cuda

Implementation of the FDTD Method Based on Lorentz-Drude Dispersive Model on Gpu for Plasmonics Applications

Gpu Implementation of Split-Field Finite-Difference Time-Domain Method for Drude-Lorentz Dispersive Media

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