Parallel Acceleration Technique For Electromagnetic Scattering Problems Based On GPU Computing Platforms

The calculation of the electromagnetic scattering of targets, especially the radar cross section (RCS) prediction and the inverse synthetic aperture radar (ISAR) imaging, has important significance for the national defense construction. It is also a hot research topic in computational electromagnetics. However, it is very time-consuming for analyzing the electromagnetic scattering characteristic of the realistic targets (e.g., airplanes and ships) at high frequency due to extensive computation and insufficient processing power.In order to solve the electromagnetic scattering problems fast, this thesis adopts the real time ray tracing algorithm in computer graphics, and utilizes the GPU, the heterogeneous CPU-GPU architecture and the GPU cluster to accelerate the frequency-domain methods by exploiting the powerfully parallel computing ability of the GPU, respectively.The proposed CUDA-based multiresolution shooting and bouncing ray (MSBR) method with the kd-tree acceleration structure is fully implemented on the GPU to accelerate the SBR method. The multiresolution grid algorithm can greatly reduce the total number of ray tubes, as it adaptively adjusts the density of ray tubes for regions with different complexities of their structures, while the kd-tree acceleration structure can highly decrease the number of ray-patch intersection tests. We also present a CUDA-based MOM, which calculates the singular and non-singular elements of impedance matrix separately to avoid the performance degradation resulting from the branch divergence. Additionally, the CUBLAS library provided by CUDA is applied to develop the BiCGSTAB to efficiently solve the matrix equation.The SBR and the truncated wedge incremental length diffraction coefficients (TW-ILDC) are combined and implemented on the heterogeneous CPU-GPU architecture to fully utilize all available resources. The SBR is calculated in the GPU because numerous independent ray tubes can make full use of the massively parallel resources on the GPU, while the TW-ILDC is implemented on the CPU since it requires complex and high-precision numerical calculation to get the accurate result. As the workload and the computation time of neighboring aspect angles are similar, a dynamic load adjustment method is presented to achieve reasonable load balancing between the CPU and GPU. The proposed method provides higher accuracy and efficiency for ISAR imaging of electrically large complex targets.Finally, an efficient parallel shooting and bouncing ray (SBR) method on the GPU cluster is introduced. The parallel SBR method applies the virtual aperture partitioning scheme to overcome the drawback of angle distribution scheme. This method is not based on the assumption all the GPUs have the same performance, and it employs the computational time at the previous angle to dynamically adjust the partitioning at the current angle. This strategy not only achieves excellent load balance, but also makes the proposed method work well on the heterogeneous GPU cluster.This thesis combines the real time ray tracing algorithm in computer graphics and three parallel computing platforms, i.e. the GPU, the heterogeneous CPU-GPU architecture and the GPU cluster, to improve several frequency-domain approaches. The numerical results show the above-mentioned methods improve the accuracy, efficiency and scale of the analysis of scattering characteristic of the electrically large targets.