2016Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIERequires access

Development of FDTD simulation tool for designing micro-nanostructured based optical devices

Anil Shrestha, Genki Mizuno, Patrick Oduor, Saif ul Islam, Achyut K. Dutta, Nibir K. Dhar

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Abstract

The use of Graphics Processing Unit (GPU) for computational work has revolutionized how complex electromagnetic problems are solved. Complex problems which required supercomputers in the past for analysis can now be tackled and solved using personal computers by channeling the computational work towards GPUs instead of the traditional computer Central Processing Unit (CPU). Finite-Difference Time-Domain (FDTD) analysis, which is a computationally expensive method of solving electromagnetic problems is highly parallel in nature and can be readily executed in a GPU. We have developed an algorithm for three dimensional FDTD analysis of optical devices with micro and nano-structures using Compute Unified Device Architecture (CUDA). The developed algorithm exploits the benefits of multiple cores of GPU chips and boosts the speed of simulation without sacrificing its accuracy. We achieved a 25-fold speed up of simulation using CUDA compared to MATLAB code in CPU.

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What this paper is about

The use of Graphics Processing Unit (GPU) for computational work has revolutionized how complex electromagnetic problems are solved. Complex problems which required supercomputers in the past for analysis can now be tackled and solved using personal computers by channeling the computational work towards GPUs instead of the traditional computer Central Processing Unit (CPU). Finite-Difference Time-Domain (FDTD) analysis, which is a computationally expensive method of solving electromagnetic problems is highly parallel in nature and can be readily executed in a GPU. We have developed an algorithm for three dimensional FDTD analysis of optical devices with micro and nano-structures using Compute Unified Device Architecture (CUDA). The developed algorithm exploits the benefits of multiple cores of GPU chips and boosts the speed of simulation without sacrificing its accuracy. We achieved a 25-fold speed up of simulation using CUDA compared to MATLAB code in CPU.

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Available abstract

The use of Graphics Processing Unit (GPU) for computational work has revolutionized how complex electromagnetic problems are solved. Complex problems which required supercomputers in the past for analysis can now be tackled and solved using personal computers by channeling the computational work towards GPUs instead of the traditional computer Central Processing Unit (CPU). Finite-Difference Time-Domain (FDTD) analysis, which is a computationally expensive method of solving electromagnetic problems is highly parallel in nature and can be readily executed in a GPU. We have developed an algorithm for three dimensional FDTD analysis of optical devices with micro and nano-structures using Compute Unified Device Architecture (CUDA). The developed algorithm exploits the benefits of multiple cores of GPU chips and boosts the speed of simulation without sacrificing its accuracy. We achieved a 25-fold speed up of simulation using CUDA compared to MATLAB code in CPU.

Key concepts: CUDA, Finite-difference time-domain method, Computer science, Graphics processing unit, Computational science, Central processing unit, Graphics, General-purpose computing on graphics processing units

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