Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics

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Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as charged particle tracking, jet tagging, and clustering. An important domain for the application of these networks is the FGPA-based first layer of real-time data filtering at...

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Detalles Bibliográficos
Autores principales: Iiyama, Yutaro, Cerminara, Gianluca, Gupta, Abhijay, Kieseler, Jan, Loncar, Vladimir, Pierini, Maurizio, Qasim, Shah Rukh, Rieger, Marcel, Summers, Sioni, Van Onsem, Gerrit, Wozniak, Kinga Anna, Ngadiuba, Jennifer, Di Guglielmo, Giuseppe, Duarte, Javier, Harris, Philip, Rankin, Dylan, Jindariani, Sergo, Liu, Mia, Pedro, Kevin, Tran, Nhan, Kreinar, Edward, Wu, Zhenbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Big Data
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006281/
https://www.ncbi.nlm.nih.gov/pubmed/33791596
http://dx.doi.org/10.3389/fdata.2020.598927

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006281/
https://www.ncbi.nlm.nih.gov/pubmed/33791596
http://dx.doi.org/10.3389/fdata.2020.598927

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