JEDI-linear is a linear-complexity GNN for FPGA jet tagging that reports sub-60 ns latency, higher accuracy than prior designs, and no DSP usage while meeting HL-LHC CMS Level-1 trigger requirements.
Automatic heterogeneous quantization of deep neural networks for low-latency in- ference on the edge for particle detectors,
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JEDI-linear: Fast and Efficient Graph Neural Networks for Jet Tagging on FPGAs
JEDI-linear is a linear-complexity GNN for FPGA jet tagging that reports sub-60 ns latency, higher accuracy than prior designs, and no DSP usage while meeting HL-LHC CMS Level-1 trigger requirements.