{"title":"基于gpu加速的特征基函数法(CBFM)用于分层介质复杂平台的高效分析","authors":"Yang Su, R. Mittra","doi":"10.1109/USNC-URSI.2019.8861918","DOIUrl":null,"url":null,"abstract":"In this paper, we present a scheme for efficient numerical modeling of operating at millimeter wavelength, e.g., 30 GHz. One of the key features of the method is the GPU acceleration adapted for the Characteristic Basis Function Method (CBFM) acceleration for problems involving layered media, which to the best of our knowledge has not been done in the past.","PeriodicalId":383603,"journal":{"name":"2019 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GPU-Acceleration of Characteristic Basis Function Method (CBFM) for Efficient Analysis of Complex Platforms involving Layered Media\",\"authors\":\"Yang Su, R. Mittra\",\"doi\":\"10.1109/USNC-URSI.2019.8861918\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a scheme for efficient numerical modeling of operating at millimeter wavelength, e.g., 30 GHz. One of the key features of the method is the GPU acceleration adapted for the Characteristic Basis Function Method (CBFM) acceleration for problems involving layered media, which to the best of our knowledge has not been done in the past.\",\"PeriodicalId\":383603,\"journal\":{\"name\":\"2019 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/USNC-URSI.2019.8861918\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/USNC-URSI.2019.8861918","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GPU-Acceleration of Characteristic Basis Function Method (CBFM) for Efficient Analysis of Complex Platforms involving Layered Media
In this paper, we present a scheme for efficient numerical modeling of operating at millimeter wavelength, e.g., 30 GHz. One of the key features of the method is the GPU acceleration adapted for the Characteristic Basis Function Method (CBFM) acceleration for problems involving layered media, which to the best of our knowledge has not been done in the past.