一种基于图形处理器（GPU）的计算，采用三维时域有限差分（FDTD）方法进行电磁场分析。

A GPU-based calculation using the three-dimensional FDTD method for electromagnetic field analysis.

作者信息

Nagaoka Tomoaki, Watanabe Soichi

机构信息

Electromagnetic Compatibility Group, Applied Electromagnetic Research Center, National Institute of Information and Communications Technology, Tokyo 184-8795, Japan.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:327-30. doi: 10.1109/IEMBS.2010.5627705.

DOI:10.1109/IEMBS.2010.5627705

PMID:21096967

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.

摘要

最近，在生物医学工程的许多领域中，经常使用时域有限差分（FDTD）方法通过数字人体模型进行数值模拟。然而，FDTD计算运行速度太慢。因此，我们专注于在图形处理单元（GPGPU）上进行通用编程。使用统一计算设备架构（CUDA）在GPU上实现了三维FDTD方法。在本研究中，我们使用NVIDIA Tesla C1060作为GPGPU板。与传统CPU和向量超级计算机的性能相比，对GPU的性能进行了评估。结果表明，与使用传统CPU相比，使用GPU进行三维FDTD计算可以显著减少运行时间，即使是三维FDTD方法的原生GPU实现，而GPU/CPU速度比会随计算域和线程块大小而变化。