Speed It Up

Ong, Cen; Weldon, M.; Quiring, Scott; Maxwell, Lee M.; Hughes, Michael R.; Whelan, C.S.; Okoniewski, M.

doi:10.1109/mmm.2010.935776

Cited by 20 publications

(12 citation statements)

References 13 publications

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“…Among these, lots of works are concerned with the problems of FDTD (Finite-Difference Time-Domain) simulation of EM fields. The works published thus far [7]- [11], however, look rather limited to those with only simple calculation procedures or those without any explanation of main algorithm. If most of calculations and procedures were treatable only by basic FDTD equations such as wave propagation calculation, it would be fairly easy to extract the GPU's inherent acceleration ability, since basic FDTD algorithm is essentially suited to multi-thread parallel computing function of GPU.…”

Section: Introductionmentioning

confidence: 99%

GPU accelerated FDTD solver algorithm for radiation from MMIC passive components

Morita¹

2013

2013 International Conference on Signal Processing and Communication (Icsc)

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GPU (Graphical Processing Unit) acceleration algorithm for an FDTD (Finite-Difference Time-Domain) solver analyzing radiation from MMIC (Monolithic Microwave Integrated Circuit) passive components is presented. Total power and radiation patterns of fields not only radiated into the halfspace region but also scattered along the substrate as surface waves can be very accurately evaluated. Tangential fields on a cuboid surface enclosing objects of calculation are used as source fields for evaluating radiated fields. These source fields are obtained through use of conventional FDTD calculation of fields produced by time-harmonic wave excitation and time integration over the last one period. This source field calculation as well as usual FDTD field calculation in the whole region is done in the GPU device. Thus, about 10 times speedup ratio compared with GPU-less calculation is attained under the circumstances of two Intel Xeon(R) E5620 CPUs (total 8 cores) and one Tesla C2075 GPU. Calculation algorithm using GPU device is explained in detail. Theoretical procedures developed by the author for obtaining radiated fields from source fields are also reviewed briefly. Numerical examples are given for a step index low pass filter.

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Section: Introductionmentioning

confidence: 99%

GPU accelerated FDTD solver algorithm for radiation from MMIC passive components

Morita¹

2013

2013 International Conference on Signal Processing and Communication (Icsc)

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“…in 2004 . From then on, many approaches for solving FDTD on GPUs have been experimented , and a commercial release is available as well . Besides the finite‐difference frequency‐domain method , also the finite element method (FEM) , the transmission line modeling , the alternating direction implicit technique , and the multilevel fast multipole algorithm have demonstrated efficient performance when implemented on GPUs.…”

Section: Introductionmentioning

confidence: 99%

“…In all of the aforementioned publications, huge speed‐up factors are achieved when the GPU implementation is compared with the reference CPU code. For instance, looking at the most recent works, speed‐ups of about 20×, 6×, and 30× are reported respectively in FEM , MoM , and FDTD simulations. A recent trend in GPU computing is the exploitation of multi‐GPU clusters for large‐scale simulations.…”

Section: Introductionmentioning

confidence: 99%

GPU‐based acceleration of computational electromagnetics codes

Donno

Esposito

Monti

et al. 2012

Int J Numerical Modelling

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SUMMARY The solution of large and complex electromagnetic (EM) problems often leads to a substantial demand for high‐performance computing resources and strategies. This is true for a wide variety of numerical methods and applications, ranging from EM compatibility to radio‐coverage, circuit modeling, and optimization of components. In the last decades, graphics processing units (GPUs) have gained popularity in scientific computing as a low‐cost and powerful parallel architecture. This paper gives an overview of the main efforts of researchers to port computational electromagnetics (CEM) codes to GPU. Moreover, GPU implementation aspects of two well‐known techniques, namely the finite‐difference time domain (FDTD) and the method of moments (MoM), are investigated. The impressive speed‐ups achieved (up to 60× and 25× for FDTD and MoM, respectively) demonstrate the effectiveness of GPUs in accelerating CEM codes. Copyright © 2012 John Wiley & Sons, Ltd.

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“…As commercial sectors like Remcom, Computer Simulation Technology (CST), Acceleware, SPEAG, and Agilent have integrated the GPU-accelerated FDTD technique into their software packages for the analysis of electromagnetic fields in normal and complex media, researchers in academia have also focused on taking advantage of inherent attributes of the GPUs for parallel computing. Such implementations that use the CUDA technology include the works presented in [3] and [4] originally, and the research presented by Sypek et al for a TM z solution of electromagnetic fields [5], the double precision implementation of the FDTD on the Tesla GPU [6], and the work reported by Okoniewski's group [7], more recently.…”

Section: Introductionmentioning

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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Speed It Up

Cited by 20 publications

References 13 publications

GPU accelerated FDTD solver algorithm for radiation from MMIC passive components

GPU accelerated FDTD solver algorithm for radiation from MMIC passive components

GPU‐based acceleration of computational electromagnetics codes

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

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