Numerical simulation of resonance structures with FDTD algorithms based on GPU B-CALM and CPU Meep
Optical and Quantum Electronics, ISSN: 1572-817X, Vol: 46, Issue: 8, Page: 1021-1026
2014
- 4Citations
- 5Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Simulation time is one of the bottlenecks of finite-difference-time-domain (FDTD) method. There are several ways of reducing the simulation time, one of which is the usage of graphical processing unit (GPU). Thus in this paper we present comparison between two free FDTD software packages. One is based on central processing unit and other is based on GPU. The 3D test structures we analyzed were metallic rectangular cavity resonator and microring resonator based refractive index sensor. The comparison between two FDTD software packages is made with regard to simulation time and numerical accuracy. It is shown that both packages agree in numerical results and that GPU based FDTD implementation performs same simulation up to 18 times faster. © 2013 Springer Science+Business Media New York.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84904256496&origin=inward; http://dx.doi.org/10.1007/s11082-013-9816-8; http://link.springer.com/10.1007/s11082-013-9816-8; http://link.springer.com/content/pdf/10.1007/s11082-013-9816-8; http://link.springer.com/content/pdf/10.1007/s11082-013-9816-8.pdf; http://link.springer.com/article/10.1007/s11082-013-9816-8/fulltext.html; https://dx.doi.org/10.1007/s11082-013-9816-8; https://link.springer.com/article/10.1007/s11082-013-9816-8
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know