Abstract-We present a three-dimensional finite difference time domain (FDTD) method on graphics processing unit (GPU) for plasmonics applications. For the simulation of plasmonics devices, the Lorentz-Drude (LD) dispersive model is incorporated into Maxwell equations, while the auxiliary differential equation (ADE) technique is applied to the LD model. Our numerical experiments based on typical domain sizes as well as plasmonics environment demonstrate that our implementation of the FDTD method on GPU offers significant speed up as compared to the traditional CPU implementations.

The Lorentz–Drude model incorporated Maxwell equations are simulated by using the three-dimensional finite difference time domain (FDTD) method and the method is parallelized on multiple graphics processing units (GPUs) for plasmonics applications. The compute unified device architecture (CUDA) is used for GPU parallelization. The Lorentz–Drude (LD) model is used to simulate the dispersive nature of materials in plasmonics domain and the auxiliary differential equation (ADE) approach is used to make it consistent with time domain Maxwell equations. Different aspects of multiple GPUs for the FDTD method are presented such as comparison of different numbers of GPUs, transfer time in between them, synchronous, and asynchronous passing. It is shown that by using multiple GPUs in parallel fashion, significant reduction in the simulation time can be achieved as compared to the single GPU.