Accelerated Finite Element Method Solver for RCS Analysis Using CUDA-Based Parallel Computing

Abstract

When addressing large-scale electromagnetic problems using the finite element method (FEM), the resulting matrices are typically sparse, necessitating numerous sparse matrix-vector multiplication (SpMV) operations. To handle this efficiently, research has focused on leveraging large-scale parallel processing with graphics processing units (GPUs). These GPUs can be controlled directly using NVIDIA’s Compute Unified Device Architecture (CUDA). In this paper, we analyze electromagnetic scattering for dielectric and dielectric-coated structures using iterative solvers with FEM. To accelerate the handling of the large-scale matrices generated during this process, we employ compressed sparse row (CSR) format, various preconditioners, and CUDA-based GPU parallelization. We verify the accuracy of our results by comparing them with those obtained using the commercial electromagnetic software High Frequency Structure Simulator (HFSS) and our custom-developed MATLAB-based FEM code. Performance improvements are assessed by comparing these results with those from MATLAB’s backslash direct solver under single-core processing conditions.

Keywords

• Finite element method
• absorbing boundary conditions
• radar cross section
• parallel processing
• CUDA