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Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml
Recurrent neural networks have been shown to be effective architectures for many tasks in high energy physics, and thus have been widely adopted. Their use in low-latency environments has, however, been limited as a result of the difficulties of implementing recurrent architectures on field-programm...
Autores principales: | Khoda, Elham E., Rankin, Dylan, de Lima, Rafael Teixeira, Harris, Philip, Hauck, Scott, Hsu, Shih-Chieh, Kagan, Michael, Loncar, Vladimir, Paikara, Chaitanya, Rao, Richa, Summers, Sioni, Vernieri, Caterina, Wang, Aaron |
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Lenguaje: | eng |
Publicado: |
2022
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/2632-2153/acc0d7 http://cds.cern.ch/record/2816114 |
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