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Content Provider | IEEE Xplore Digital Library |
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Author | Nagaoka, T. Watanabe, S. |
Copyright Year | 2010 |
Description | Author affiliation: Electromagnetic Compatibility Group, Applied Electromagnetic Research Center, National Institute of Information and Communications Technology, Tokyo 184-8795, Japan (Nagaoka, T.; Watanabe, S.) |
Abstract | Numerical simulations with the numerical human model using the finite-difference time domain (FDTD) method have recently been performed frequently in a number of fields in biomedical engineering. However, the FDTD calculation runs too slowly. We focus, therefore, on general purpose programming on the graphics processing unit (GPGPU). The three-dimensional FDTD method was implemented on the GPU using Compute Unified Device Architecture (CUDA). In this study, we used the NVIDIA Tesla C1060 as a GPGPU board. The performance of the GPU is evaluated in comparison with the performance of a conventional CPU and a vector supercomputer. The results indicate that three-dimensional FDTD calculations using a GPU can significantly reduce run time in comparison with that using a conventional CPU, even a native GPU implementation of the three-dimensional FDTD method, while the GPU/CPU speed ratio varies with the calculation domain and thread block size. |
Starting Page | 327 |
Ending Page | 330 |
File Size | 623327 |
Page Count | 4 |
File Format | |
ISBN | 9781424441235 |
ISSN | 1557170X |
DOI | 10.1109/IEMBS.2010.5627705 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2010-08-31 |
Publisher Place | Argentina |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Graphics processing unit Finite difference methods Kernel Time domain analysis Instruction sets Numerical models Humans |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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