{"title":"Fast computation of finite difference generated time-domain green's functions of layered media using OpenAcc on graphics processors","authors":"S. R. M. Rostami, M. Ghaffari‐Miab","doi":"10.1109/IRANIANCEE.2017.7985300","DOIUrl":null,"url":null,"abstract":"This paper presents a graphics processing unit (GPU) implementation of finite difference generated time domain green's functions (TDGFs) to evaluate vector potential of layered media. The media which considered is truncated by a perfect electric conductor (PEC) and symmetry axis. GPU parallel implementation is considered using OpenAcc and the efficacy of GPU for implementing this algorithm is illustrated. The accuracy of the proposed method is validated by comparing the results with that of a serial implementation of problem on central processing unit (CPU). The comparison with CPU one core execution time is presented and it is shown that using OpenAcc leads to significant speed-up without losing the accuracy.","PeriodicalId":161929,"journal":{"name":"2017 Iranian Conference on Electrical Engineering (ICEE)","volume":"313 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Iranian Conference on Electrical Engineering (ICEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRANIANCEE.2017.7985300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This paper presents a graphics processing unit (GPU) implementation of finite difference generated time domain green's functions (TDGFs) to evaluate vector potential of layered media. The media which considered is truncated by a perfect electric conductor (PEC) and symmetry axis. GPU parallel implementation is considered using OpenAcc and the efficacy of GPU for implementing this algorithm is illustrated. The accuracy of the proposed method is validated by comparing the results with that of a serial implementation of problem on central processing unit (CPU). The comparison with CPU one core execution time is presented and it is shown that using OpenAcc leads to significant speed-up without losing the accuracy.