{"title":"计算统一器件架构的GPU高速FDTD仿真算法","authors":"N. Takada, T. Shimobaba, N. Masuda, T. Ito","doi":"10.1109/APS.2009.5171728","DOIUrl":null,"url":null,"abstract":"We proposed an FDTD algorithm for GPU with CUDA. Our GPU-FDTD algorithm performed high-speed FDTD simulation using GPU with CUDA, and maintained single-floating point accuracy. In the larger computational domain, the speedup factor becomes worse. The result suggests that the bottleneck of the FDTD simulation is memory bandwidth. Our GPU-FDTD algorithm can be applied to 3-D FDTD simulation. In future, we plan to implement our GPU-FDTD algorithm to the 3-D FDTD simulation.","PeriodicalId":213759,"journal":{"name":"2009 IEEE Antennas and Propagation Society International Symposium","volume":"419 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"High-speed FDTD simulation algorithm for GPU with compute unified device architecture\",\"authors\":\"N. Takada, T. Shimobaba, N. Masuda, T. Ito\",\"doi\":\"10.1109/APS.2009.5171728\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We proposed an FDTD algorithm for GPU with CUDA. Our GPU-FDTD algorithm performed high-speed FDTD simulation using GPU with CUDA, and maintained single-floating point accuracy. In the larger computational domain, the speedup factor becomes worse. The result suggests that the bottleneck of the FDTD simulation is memory bandwidth. Our GPU-FDTD algorithm can be applied to 3-D FDTD simulation. In future, we plan to implement our GPU-FDTD algorithm to the 3-D FDTD simulation.\",\"PeriodicalId\":213759,\"journal\":{\"name\":\"2009 IEEE Antennas and Propagation Society International Symposium\",\"volume\":\"419 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Antennas and Propagation Society International Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APS.2009.5171728\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Antennas and Propagation Society International Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APS.2009.5171728","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
High-speed FDTD simulation algorithm for GPU with compute unified device architecture
We proposed an FDTD algorithm for GPU with CUDA. Our GPU-FDTD algorithm performed high-speed FDTD simulation using GPU with CUDA, and maintained single-floating point accuracy. In the larger computational domain, the speedup factor becomes worse. The result suggests that the bottleneck of the FDTD simulation is memory bandwidth. Our GPU-FDTD algorithm can be applied to 3-D FDTD simulation. In future, we plan to implement our GPU-FDTD algorithm to the 3-D FDTD simulation.