Parallel SVD-CBFM based on GPU acceleration

The singular value decomposition characteristic basis function method (SVD-CBFM) is usually used to solve the electromagnetic scattering problems. When the number of unknowns increases, the memory and computation time consumed become insufferable. The parallel SVD-CBFM solution on graphics processing unit (GPU) is implemented by the compute unified device architecture (CUDA) technology in this paper. The acceleration ratio of parallel SVD-CBFM comparing with traditional central processing unit (CPU) is also analyzed. Numerical results show that the speed of impedance matrix filling and reduced matrix filling is greatly improved.