Parallel 3D Finite Difference Time Domain Simulations on Graphics Processors with Cuda

In this paper, the Graphics Processing Unit(GPU) computing together with Cluster of Workstations(COW) techniques are discussed. Based on which a high efficiency hardware accelerated Finite-Difference Time-Domain (FDTD) algorithm has been developed and implemented in two nodes COW system. Two typical EM simulation examples have been simulated. The results show good agreement between the GPU+COW scheme and the traditional CPU computing while at least 60 times speedup has been achieved.

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Parallel 3D Finite Difference Time Domain Simulations on Graphics Processors with Cuda

Cited by 8 publications

References 8 publications

Hybrid CPU-GPU computation of adjoint derivatives in time domain

Hybrid CPU-GPU computation of adjoint derivatives in time domain

A comparison of the FDTD algorithm implemented on an integrated GPU versus a GPU configured as a co-processor

Research on GPU Cluster acceleration of FDTD algorithm

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