An Accurate and Efficient Finite Element-Boundary Integral Method With GPU Acceleration for 3-D Electromagnetic Analysis
An Accurate and Efficient Finite Element-Boundary Integral Method With GPU Acceleration for 3-D Electromagnetic Analysis
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DOI：
10.1109/tap.2014.2361896
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发表时间：
2014-10
影响因子：
5.7
通讯作者：
Jian Guan;Su Yan;Jianming Jin
中科院分区：
文献类型：
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作者：
Jian Guan;Su Yan;Jianming Jin
针对复杂结构和材料的电磁场问题，提出了一种基于图形处理器（GPU）加速的高精度有限元-边界积分（FE-BI）方法。为了提高FE-BI方法的精度，提出了一种混合检验方案，即采用Rao-Wilton-Glisson函数和Buffa-Christiansen函数作为检验函数。提出了一种基于吸收边界条件（ABC）的预条件子来加速迭代解的收敛。为了进一步提高总的计算效率，一个GPU加速的多层快速多极算法（MLFMA）被应用到迭代求解。通过对几个典型目标的雷达散射截面（RCS）计算，验证了该方法的数值精度，同时也表明该方法不仅不受内共振的影响，而且比传统的FE-BI方法具有更好的收敛性。所提出的方法的能力和效率进行了分析，通过几个数值例子，包括一个大的电介质涂层的球体，部分人体，和涂层的导弹状物体。与基于8线程CPU的算法相比，GPU加速的FE-BI-MLFMA算法可以实现高达25.5倍的总加速比。
An accurate and efficient finite element-boundary integral (FE-BI) method with graphics processing unit (GPU) acceleration is presented for solving electromagnetic problems with complex structures and materials. A mixed testing scheme, in which the Rao-Wilton-Glisson and the Buffa-Christiansen functions are both employed as the testing functions, is first presented to improve the accuracy of the FE-BI method. An efficient absorbing boundary condition (ABC)-based preconditioner is then proposed to accelerate the convergence of the iterative solution. To further improve the efficiency of the total computation, a GPU-accelerated multilevel fast multipole algorithm (MLFMA) is applied to the iterative solution. The radar cross sections (RCS) of several benchmark objects are calculated to demonstrate the numerical accuracy of the solution and also to show that the proposed method not only is free of interior resonance corruption, but also has a better convergence than the conventional FE-BI methods. The capability and efficiency of the proposed method are analyzed through several numerical examples, including a large dielectric coated sphere, a partial human body, and a coated missile-like object. Compared with the 8-threaded CPU-based algorithm, the GPU-accelerated FE-BI-MLFMA algorithm can achieve a total speedup up to 25.5 times.