{"title":"使用多 GPU 的新型并行频域有限差分算法","authors":"Yijing Wang;Xinbo He;Bin Wei","doi":"10.1109/LMWT.2024.3414598","DOIUrl":null,"url":null,"abstract":"This letter presents a parallel frequency-domain finite-difference (FDFD) algorithm based on multi-graphic processing unit (GPU) applied to electromagnetic scattering computations to enhance the computational efficiency of the algorithm. The proposed algorithm parallelizes the solution of large-scale sparse matrices, distributing threads to the matrix-vector and vector-vector multiplication operations within decomposed sub-matrices to reduce the computational time. Moreover, we configure the OpenMP to optimize communication transfer between multiple GPUs, thereby improving computational efficiency. The simulation results show that compared with the conventional FDFD method, the proposed algorithm can enhance computational efficiency while ensuring accuracy.","PeriodicalId":73297,"journal":{"name":"IEEE microwave and wireless technology letters","volume":"34 8","pages":"971-974"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Parallel Frequency-Domain Finite-Difference Algorithm Using Multi-GPU\",\"authors\":\"Yijing Wang;Xinbo He;Bin Wei\",\"doi\":\"10.1109/LMWT.2024.3414598\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This letter presents a parallel frequency-domain finite-difference (FDFD) algorithm based on multi-graphic processing unit (GPU) applied to electromagnetic scattering computations to enhance the computational efficiency of the algorithm. The proposed algorithm parallelizes the solution of large-scale sparse matrices, distributing threads to the matrix-vector and vector-vector multiplication operations within decomposed sub-matrices to reduce the computational time. Moreover, we configure the OpenMP to optimize communication transfer between multiple GPUs, thereby improving computational efficiency. The simulation results show that compared with the conventional FDFD method, the proposed algorithm can enhance computational efficiency while ensuring accuracy.\",\"PeriodicalId\":73297,\"journal\":{\"name\":\"IEEE microwave and wireless technology letters\",\"volume\":\"34 8\",\"pages\":\"971-974\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE microwave and wireless technology letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10570323/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE microwave and wireless technology letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10570323/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
A New Parallel Frequency-Domain Finite-Difference Algorithm Using Multi-GPU
This letter presents a parallel frequency-domain finite-difference (FDFD) algorithm based on multi-graphic processing unit (GPU) applied to electromagnetic scattering computations to enhance the computational efficiency of the algorithm. The proposed algorithm parallelizes the solution of large-scale sparse matrices, distributing threads to the matrix-vector and vector-vector multiplication operations within decomposed sub-matrices to reduce the computational time. Moreover, we configure the OpenMP to optimize communication transfer between multiple GPUs, thereby improving computational efficiency. The simulation results show that compared with the conventional FDFD method, the proposed algorithm can enhance computational efficiency while ensuring accuracy.