FPGA-accelerated machine learning inference as a service for particle physics computing

Large-scale particle physics experiments face challenging demands for high-throughput computing resources both now and in the future. New heterogeneous computing paradigms on dedicated hardware with increased parallelization, such as Field Programmable Gate Arrays (FPGAs), offer exciting solutions w...

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Detalles Bibliográficos
Autores principales: Duarte, Javier, Harris, Philip, Hauck, Scott, Holzman, Burt, Hsu, Shih-Chieh, Jindariani, Sergo, Khan, Suffian, Kreis, Benjamin, Lee, Brian, Liu, Mia, Lončar, Vladimir, Ngadiuba, Jennifer, Pedro, Kevin, Perez, Brandon, Pierini, Maurizio, Rankin, Dylan, Tran, Nhan, Trahms, Matthew, Tsaris, Aristeidis, Versteeg, Colin, Way, Ted W., Werran, Dustin, Wu, Zhenbin
Lenguaje:eng
Publicado: 2019
Materias:
physics.ins-det
Detectors and Experimental Techniques
physics.comp-ph
Other Fields of Physics
hep-ex
Particle Physics - Experiment
physics.data-an
Acceso en línea:https://dx.doi.org/10.1007/s41781-019-0027-2
http://cds.cern.ch/record/2695229

Internet

https://dx.doi.org/10.1007/s41781-019-0027-2
http://cds.cern.ch/record/2695229

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