[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118653-en":3,"doc-seo-118653-105":30,"detail-sidebar-cat-0-en-105":84},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118653,1099514068365,"Aurelia","https://ap-avatar.wpscdn.com/avatar/10000253d8d9f28188e?_k=1776742907772140068",8,"Research & Report","Electromagnetic simulations of antennas on GPUs for machine learning applications","This research proposes a GPU-powered antenna electromagnetic simulation framework for machine learning applications, leveraging the open-source gprMax software. Simulation outputs are compared with those from commercial EM tools, targeting efficient generation of large antenna datasets using predefined or randomized geometry parameters. Because EM simulations are computationally intensive and machine learning is sample-hungry, GPUs accelerate data production within practical time limits. The study also evaluates multiple machine learning and deep learning models for antenna parameter estimation, reporting major GPU performance gains over CPUs and comparable results to commercial software when spatial resolution is sufficiently fine.","Turkish Journal of Electrical Engineering and Computer Sciences  \n\n| Volume 33  Number 5 | Article 5 |\n| --- | --- |\n| 9-25-2025\u003Cbr>Electromagnetic simulations of antennas on GPUs for machine learning applications\u003Cbr>MURAT TEMİZ\u003Cbr>VEMUND BAKKEN\u003Cbr>Follow this and additional works at: [https://journals.tubitak.gov.tr/elektrik](https://journals.tubitak.gov.tr/elektrik) |  |\n\nRecommended Citation  \nTEMİZ, M, & BAKKEN, V (2025) . Electromagnetic simulations of antennas on GPUs for machine learning applications. Turkish Journal of Electrical Engineering and Computer Sciences 33 (5): 574-593.  \n[https://doi.org/10.55730/1300-0632.4145](https://doi.org/10.55730/1300-0632.4145)  \nThis work is licensed under a Creative Commons Attribution 4.0 International License.  \nThis Research Article is brought to you for free and open access by TÜBİTAK Academic Journals. It has been accepted for inclusion in Turkish Journal of Electrical Engineering and Computer Sciences by an authorized editor of TÜBİTAK Academic Journals. For more information, please contact [academic.publications@tubitak.gov.tr](academic.publications@tubitak.gov.tr)  \n\n|  | Turkish Journal of Electrical Engineering & Computer Sciences\u003Cbr>[http:/ / journals. tu bit ak. gov. tr/ele kt rik/](http:/ / journals. tu bit ak. gov. tr/ele kt rik/)\u003Cbr>\u003Cbr>Research Article |  |  | Turk J Elec Eng & Comp Sci (2025) 33: 574 – 593\u003Cbr>© TÜBİTAK\u003Cbr>doi:10.55730/1300-0632.4145 |  |\n| --- | --- | --- | --- | --- | --- |\n| Electromagnetic simulations of antennas on GPUs for machine learning\u003Cbr>applications\u003Cbr>Murat TEMİZ1 ,2 , ∗􀁋, Vemund BAKKEN3􀁋\u003Cbr>1 Department of Electrical and Electronics Engineering, Faculty of Engineering,\u003Cbr>Middle East Technical University, Ankara, Turkiye\u003Cbr>2 Department of Electronic and Electrical Engineering, University College London, London, United Kingdom\u003Cbr>3 ONiO AS, Oslo, Norway |  |  |  |  |  |\n| Received: 19.02.2025 |  | • | Accepted/Published Online: 08.09.2025 | • | Final Version: 25.09.2025 |\n| Abstract: This study proposes an antenna simulation framework powered by graphics processing units (GPUs) based on an open-source electromagnetic (EM) simulation software (gprMax) for machine learning applications of antenna design and optimization. Furthermore, it compares the simulation results with those obtained through commercial EM software. The proposed software framework for machine learning and surrogate model applications will produce antenna data sets consisting of a large number of antenna simulation results using GPUs. Although machine learning methods can attain the optimum solutions for many problems, they are known to be data-hungry and require a great deal of samples for the training stage of the algorithms. However, producing a sufficient number of training samples in EM applications within a limited time is challenging due to the high computational complexity of EM simulations. Therefore, GPUs are utilized in this study to simulate a large number of antennas with predefined or random antenna shape parameters to produce data sets. Moreover, this study also compares various machine learning and deep learning models in terms of antenna parameter estimation performance. This study demonstrates that an entry-level GPU substantially outperformsa high-end CPU in terms of computational performance, while a high-end gaming GPU can achieve around 18 times more computational performance compared to a high-end CPU. Moreover, it is shown that the open-source EM simulation software can deliver similar results to those obtained via commercial software in the simulation of microstrip antennas when the spatial resolution of the simulations is sufficiently fine.\u003Cbr>Key words: Antenna simulations, electromagnetic, machine learning, open-source, gprMax\u003Cbr>1. Introduction\u003Cbr>EM simulation software and libraries are paramount for antenna and EM research and engineering since the fabrication and measurements of antenna prototypes are relatively expensive and time-consumin","cbCaicLiaifLeLzv","https://ap.wps.com/l/cbCaicLiaifLeLzv","pdf",1600976,1,21,"English","en",105,"# Abstract\n# 1. Introduction\n## EM simulation software and libraries\n## Commercial vs open-source tools\n## Motivation for GPU-accelerated dataset generation","[{\"question\":\"What performance and accuracy comparisons are reported?\",\"answer\":\"An entry-level GPU substantially outperforms a high-end CPU, and a high-end gaming GPU can deliver about 18× more computational performance; open-source gprMax is also reported to match commercial software results for microstrip antennas when simulation spatial resolution is sufficiently fine.\"}]","Electromagnetic simulations of antennas on GPUs for machine learning applications | PDF",1785684726,53,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":79,"head_meta":81,"extra_data":83,"updated_unix":28},"electromagnetic-simulations-of-antennas-on-gpus-for-machine-learning-applications","",{"@graph":36,"@context":78},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/electromagnetic-simulations-of-antennas-on-gpus-for-machine-learning-applications/118653/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04","2026-08-02",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72],{"name":73,"@type":74,"acceptedAnswer":75},"What performance and accuracy comparisons are reported?","Question",{"text":76,"@type":77},"An entry-level GPU substantially outperforms a high-end CPU, and a high-end gaming GPU can deliver about 18× more computational performance; open-source gprMax is also reported to match commercial software results for microstrip antennas when simulation spatial resolution is sufficiently fine.","Answer","https://schema.org",{"og:url":52,"og:type":80,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":82,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":85},[86,90,94,98,103,108,113,116,121,124,128],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":87,"show_sort_weight":88,"slug":89},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":91,"show_sort_weight":92,"slug":93},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Exam",70,"exam",{"id":99,"doc_module":4,"doc_module_name":46,"category_name":100,"show_sort_weight":101,"slug":102},5,"Comic",60,"comic",{"id":104,"doc_module":4,"doc_module_name":46,"category_name":105,"show_sort_weight":106,"slug":107},6,"Technology",50,"technology",{"id":109,"doc_module":4,"doc_module_name":46,"category_name":110,"show_sort_weight":111,"slug":112},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":114,"slug":115},30,"research-report",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},9,"Religion & Spirituality",20,"religion-spirituality",{"id":119,"doc_module":4,"doc_module_name":46,"category_name":122,"show_sort_weight":119,"slug":123},"World Cup","world-cup",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":125,"slug":127},10,"Lifestyle","lifestyle",{"id":129,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":99,"slug":131},19,"General","general"]