1 citations · 1 across the 3 of their papers we have counts for
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FPGA-based muon shower identification and graph neural network tracking algorithms for HL-LHC triggers
Daniel Estrada, Elena Aller, Andrea Cardini +3
This work presents two hardware-accelerated strategies for the upgrade of the CMS Level-1 Trigger (L1T) to target efficiency losses due to highly energetic radiating muons and unco…
Integer Quantization of Graph Neural Networks for Real-Time FPGA Track Finding
Andrea Cardini, Pelayo Leguina, Elena Aller +1
Real-time track finding for displaced-muon signatures in the CMS Level-1 trigger must operate under strict fixed-latency constraints of 12.5 s while processing high-throughput d…
Using AI on FPGAs for the CMS Overlap Muon Track Finder for the HL-LHC
Pelayo Leguina, Santiago Folgueras, Andrea Cardini +1
Operating the CMS Level-1 trigger under the intense conditions of the High-Luminosity Large Hadron Collider -- with approximately 63~Tb/s of input and a fixed 12.5~s latency --…