GPU-based 3D-FDTD computation for electromagnetic field dosimetry

Numerical dosimetry with the computational human model using the finite-difference time-domain (FDTD) method has recently been used for a safety assessment of electromagnetic field applications. However, the FDTD calculation runs very slowly and requires a large amount of computational memory. We focus, therefore, on general purpose programming on the graphics processing unit (GPGPU). We implemented the three-dimensional (3D) FDTD method on GPUs using Compute Unified Device Architecture (CUDA). In this study, we used the NVIDIA Tesla C2070 as a GPGPU board and tested the performance of FDTD computation on GPUs. The results indicated that while the single GPU/CPU speed ratio varies depending on the calculation domain, 3D-FDTD computation using a GPU requires significantly less run time than that using a conventional CPU. We confirmed that the FDTD computation on a multi-GPU is much faster than that on a single GPU, and we also found that eight GPUs can compute faster than a vector supercomputer.