Finite Difference Generated Transient Potentials of Open-Layered Media by Parallel Computing Using OpenMP, MPI, OpenACC, and CUDA

Abstract

The implementation of time-domain Green’s functions (TDGFs) in the graphics processing unit (GPU) and the central processing unit (CPU) using a finite-difference scheme is shown. The TDGFs represent the transient electric scalar and magnetic vector potentials due to a horizontal electric dipole (HED) in open-layered media. The layered media is bounded with a perfectly matched layer (PML), symmetry axis, and perfect electric conductor (PEC). We adopted four different parallel approaches as follows: 1) open multiprocessing (OpenMP) CPU implementation; 2) message passing interface (MPI) CPU implementation; 3) open accelerators (OpenACC) GPU implementation; and 4) compute unified device architecture (CUDA) GPU implementation. The accuracy and efficiency of the utilized programming models are validated by comparing and verifying the obtained results using a sequential CPU implementation. Compared to single threaded CPU implementation, speed-ups obtained by the OpenMP, MPI, OpenACC, and CUDA programming models are $4.8\times $ , $6.12\times $ , $45.97\times $ , and $96.53\times $ higher, respectively. The final result shows that GPU implementation leads to a considerable speed-up while the solution’s accuracy is fixed.