Multiple-Gpu-Based Frequency-Dependent Finite-Difference Time Domain Formulation Using Matlab Parallel Computing Toolbox

Shao, Wenbo; McCollough, William J.

doi:10.2528/pierm17071704

Cited by 8 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The simulation was based on a frequency-dependence finite difference time-domain method [ 28 ]. The time-domain data were then converted to frequency domain by a Fourier transform, and then the data at a certain frequency were extracted.…”

Section: Resultsmentioning

confidence: 99%

Effect of Coupling Medium on Penetration Depth in Microwave Medical Imaging

Shao

Zhou²

2022

Diagnostics

Self Cite

View full text Add to dashboard Cite

In microwave medical imaging, the human skin reflects most of microwave energy due to the impedance mismatch between the air and the body. As a result, only a small portion of the microwave energy can enter the body and work for medical purpose. One solution to tackle this issue is to use a coupling (or matching) medium, which can reduce unwanted reflections on the skin and meanwhile improve spatial imaging resolution. A few types of fluids were measured in this paper for their dielectric properties between 500 MHz and 13.5 GHz. Measurements were performed by a Keysight programmable network analyzer (PNA) with a dielectric probe kit, and dielectric constant and conductivity of the fluids were presented in this paper. Then, quantitative computations were exercised to present the attenuations due to the reflection on the skin and to the loss in each coupling medium, based on the measured liquid dielectric values. Finally, electromagnetic simulations verified that the coupling liquid can allow more microwave energy to enter the body to allow for a more efficient medical examination.

show abstract

Section: Resultsmentioning

confidence: 99%

Effect of Coupling Medium on Penetration Depth in Microwave Medical Imaging

Shao

Zhou²

2022

Diagnostics

Self Cite

View full text Add to dashboard Cite

show abstract

“…Multi-GPU systems have been used for many scientific problems and applications, including 3D finite-difference time domain [Shao and McCollough 2017;Zhou et al 2013], stencil computations [Sourouri et al 2015], PDE solvers [Malahe 2016], fluid simulation [Chu et al 2017;Hutter et al 2014;Liu et al 2016], and material point methods [Wang et al 2020]. Many of them are based on domain decomposition, which divides the computational region into sub-regions, then solves each sub-region independently on each GPU.…”

Section: Parallel Algorithmsmentioning

confidence: 99%

P-Cloth: Interactive Complex Cloth Simulation on Multi-GPU Systems using Dynamic Matrix Assembly and Pipelined Implicit Integrators

Li,

Tang,

Tong

et al. 2020

Preprint

View full text Add to dashboard Cite

nnnnnnn be handled on a single GPU due to memory limitations. We have evaluated the performance with two multi-GPU workstations (with 4 and 8 GPUs, respectively) on cloth meshes with 0.5 − 1.65M triangles. Our approach can reliably handle the collisions and generate vivid wrinkles and folds at 2 − 5 fps, which is significantly faster than prior cloth simulation systems. We observe almost linear speedups with respect to the number of GPUs.

show abstract

“…Se encuentran planteamientos MPI (message passing interface) -OpenMP [10]-GPU para calcular RCS con FDTD, que consiguen reducir el tiempo de cálculo de 3dias a 0.8h (RCS de un F-117) [11]. Las ventajas en el manejo de figuras y gráficos, así como el desarrollo de toolbox permiten finalmente la paralelización con Matlab [12], [13], [14].…”

Section: Introductionunclassified

Nvidia CUDA parallel processing of large FDTD meshes in a desktop computer

Calatayud

Navarro-Modesto

Navarro

et al. 2020

Proceedings of the 10th Euro-American Conference on Telematics and Information Systems

View full text Add to dashboard Cite

The Finite Difference in Time Domain numerical (FDTD) method is a well know and mature technique in computational electrodynamics. Usually FDTD is used in the analysis of electromagnetic structures, and antennas. However still there is a high computational burden, which is a limitation for use in combination with optimization algorithms. The parallelization of FDTD to calculate in GPU is possible using Matlab and CUDA tools. For instance, the simulation of a planar array, with a three dimensional FDTD mesh 790x276x588, for 6200 time steps, takes one day -elapsed time-using the CPU of an Intel Core i3 at 2.4GHz in a personal computer, 8Gb RAM. This time is reduced 120 times when the calculation is parallelized and carried out in a Graphics Processing Unit (GPU) NVIDIA GeForce GTX 1080 Ti 11264 MB GDDR 5X. The elapsed time is reduced substantially, but also the simplicity of calculation and usefulness of a Matlab implementation. The elapsed time reduction is so substantial that the FDTD-Matlab-CUDA can be combined with optimization algorithms.

show abstract

Multiple-Gpu-Based Frequency-Dependent Finite-Difference Time Domain Formulation Using Matlab Parallel Computing Toolbox

Cited by 8 publications

References 12 publications

Effect of Coupling Medium on Penetration Depth in Microwave Medical Imaging

Effect of Coupling Medium on Penetration Depth in Microwave Medical Imaging

P-Cloth: Interactive Complex Cloth Simulation on Multi-GPU Systems using Dynamic Matrix Assembly and Pipelined Implicit Integrators

Nvidia CUDA parallel processing of large FDTD meshes in a desktop computer

Contact Info

Product

Resources

About