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Multi-GPU Accelerated Admittance Method for High-Resolution Human Exposure Evaluation | IEEE Journals & Magazine | IEEE Xplore

Multi-GPU Accelerated Admittance Method for High-Resolution Human Exposure Evaluation


Abstract:

Objective: A multi-graphics processing unit (GPU) accelerated admittance method solver is presented for solving the induced electric field in high-resolution anatomical m...Show More

Abstract:

Objective: A multi-graphics processing unit (GPU) accelerated admittance method solver is presented for solving the induced electric field in high-resolution anatomical models of human body when exposed to external low-frequency magnetic fields. Methods: In the solver, the anatomical model is discretized as a three-dimensional network of admittances. The conjugate orthogonal conjugate gradient (COCG) iterative algorithm is employed to take advantage of the symmetric property of the complex-valued linear system of equations. Compared against the widely used biconjugate gradient stabilized method, the COCG algorithm can reduce the solving time by 3.5 times and reduce the storage requirement by about 40%. The iterative algorithm is then accelerated further by using multiple NVIDIA GPUs. The computations and data transfers between GPUs are overlapped in time by using asynchronous concurrent execution design. The communication overhead is well hidden so that the acceleration is nearly linear with the number of GPU cards. Results: Numerical examples show that our GPU implementation running on four NVIDIA Tesla K20c cards can reach 90 times faster than the CPU implementation running on eight CPU cores (two Intel Xeon E5-2603 processors). Conclusion: The implemented solver is able to solve large dimensional problems efficiently. A whole adult body discretized in 1-mm resolution can be solved in just several minutes. Significance: The high efficiency achieved makes it practical to investigate human exposure involving a large number of cases with a high resolution that meets the requirements of international dosimetry guidelines.
Published in: IEEE Transactions on Biomedical Engineering ( Volume: 62, Issue: 12, December 2015)
Page(s): 2920 - 2930
Date of Publication: 08 July 2015

ISSN Information:

PubMed ID: 26168429

Funding Agency:

Citations are not available for this document.

I. Introduction

The constantly increasing use of electromagnetic devices (e.g., wireless power transfer system [1], and transcranial magnetic stimulation [2] ) in our society raises public concerns over the potential adverse health effects produced by low-frequency electric and magnetic fields. It has been well recognized that strong electric fields cause stimulation of neural and muscle tissue, retinal phosphenes, as well as cardiac fibrillation [3], [4]. These concerns have led to great strides in the area of human exposure evaluation in the last few decades.

Cites in Papers - |

Cites in Papers - IEEE (4)

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1.
Chris D. Rouse, "Conservative Analytical Assessments of Localized RF Exposure From Small Magnetic Field Sources", IEEE Transactions on Electromagnetic Compatibility, vol.66, no.2, pp.392-404, 2024.
2.
Keishi Miwa, Yosuke Suzuki, Junqing Lan, Yinliang Diao, Akimasa Hirata, "A Novel Method to Predict the Maximum Electric Fields in Different Body Parts Exposed to Uniform Low-Frequency Magnetic Field", IEEE Transactions on Electromagnetic Compatibility, vol.63, no.5, pp.1640-1648, 2021.
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Lubin Feng, Dulei Zheng, Jianzhi Yu, "CUDA Optimization Method for Activation Function in Convolution Operation", 2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom), pp.519-525, 2019.
4.
Jose Gomez-Tames, Ilkka Laakso, Yuto Haba, Akimasa Hirata, Dragan Poljak, Kenichi Yamazaki, "Computational Artifacts of the In Situ Electric Field in Anatomical Models Exposed to Low-Frequency Magnetic Field", IEEE Transactions on Electromagnetic Compatibility, vol.60, no.3, pp.589-597, 2018.

Cites in Papers - Other Publishers (2)

1.
Congsheng Li, Zhenfei Ye, Yiwen Wei, Tongning Wu, "An optimized block forward‐elimination and backward‐substitution algorithm for GPU accelerated ILU preconditioner in evaluating the induced electric field during transcranial magnetic stimulation", Bioelectromagnetics, vol.40, no.4, pp.278, 2019.
2.
Dawei Li, Donald R. Wilton, David R. Jackson, Ji Chen, Hanming Wang, "Efficient computation of Green's functions for lossy uniaxial anisotropic layered media", Radio Science, vol.54, no.3, pp.196-214, 2019.
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References

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