3 papers
hep-ex2026
Real-Time Stream Compaction for Sparse Machine Learning on FPGAs
Marc Neu, Isabel Haide, Torben Ferber +1
Machine learning algorithms are being used more frequently in the first-level triggers in collider experiments, with Graph Neural Networks pushing the hardware requirements of FPGA…
physics.ins-det2025
Hardware-Accelerated GNN-based Hit Filtering for the Belle II Level-1 Trigger
Greta Heine, Fabio Mayer, Marc Neu +2
We present a hardware-accelerated hit filtering system employing Graph Neural Networks (GNNs) on Field-Programmable Gate Arrays (FPGAs) for the Belle II Level-1 Trigger. The GNN ex…
eess.SP2025
Real-Time Graph-based Point Cloud Networks on FPGAs via Stall-Free Deep Pipelining
Marc Neu, Isabel Haide, Timo Justinger +4
Graph-based Point Cloud Networks (PCNs) are powerful tools for processing sparse sensor data with irregular geometries, as found in high-energy physics detectors. However, deployin…