Accelerated GNN Tracking


The tracking of charged particles produced in collisions at colliders is a crucial aspect of the science program in the experiments. One of the primary challenges for the HL-LHC is the ability to efficiently, accurately, and rapidly perform tracking in collision events with large interaction pile-up. This project aims to improve charged-particle tracking in the ATLAS and CMS experiments through the use of accelerators such as field-programmable gate arrays (FPGAs) and machine learning algorithms such as Graph Neural Networks (GNNs).



A poster

Markus Atkinson made this poster on GNN-based Tracking and FPGA Acceleration

poster

Team

  • Markus Atkinson
  • Gage DeZoort
  • Lindsey Gray
  • Mark Neubauer
  • Isobel Ojalvo
  • Savannah Thais