Fast and resource-efficient deep neural network on fpga for the phase-ii level-0 muon barrel trigger of the atlas experiment

HIGHLIGHTS

• who: Giagu Stefano from the (UNIVERSITY) have published the research: Fast and resource-efficient Deep Neural Network on FPGA for the Phase-II Level-0 muon barrel trigger of the ATLAS experiment, in the Journal: (JOURNAL)
• what: The authors get inspiration from these and other studies but follow an approach more oriented in achieving a robust and working implementation for a specific deep neural_network architecture.
• how: Similar results are obtained with the tCNN which shows a reduction in the resolution in pT manifested by a slower rise in the efficiency curve around the . . .
  

   

  

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