Exa.TrkX: HEP Tracking at the Exascale. A DOE CompHEP project

Exa.TrkX is a follow-up to the the HEP.TrkX pilot project. It relies on the aCTS toolkit to simulate a generic HL-LHC detector, and more recently to benchmark the performance of its models. Exa.TrkX is collaborating with the FastML Lab to deploy GNN models on FPGA systems. Exa.TrkX is also collaborating with the NERSC Big Data center, and the Exalearn co-design center to demonstrate distributed training and model hyperparameter optimization at scale on HPC systems.

collaborators, partners & toolkits

June 2019 1st Exa.TrkX workshop at LBL. Indico agenda
April 2020 2nd Exa.TrkX virtual workshop. Indico agenda

meetings & workshops

Slack PRIVATE
Development github PRIVATE

Collaboration tools

Performance of a Geometric Deep Learning Pipeline for HL-LHC Particle Tracking ( Associated Code ) Eur. Phys. J. C 81, 876 (2021)

Disconnecting the Graph: Pattern Recognition at the CERN Large Hadron Collider A non-specialist introduction to Exa.TrkX methods presented at Networks for Science 2025.
Scaling Graph Neural Networks for Particle Track Reconstruction. Presented at IPDPS 2025.
EggNet: An Evolving Graph-based Graph Attention Network for Particle Track Reconstruction Presented at CHEP 2024.
TrackSorter: A Transformer-based sorting algorithm for track finding in High Energy Physics Presented at ACAT 2024 (Associated Code).
Influencer Loss: End-to-end Geometric Representation Learning for Track Reconstruction Presented at CHEP 2023.
Physics Performance of the ATLAS GNN4ITk Track Reconstruction Chain Presented at Connecting the Dots 2023 (Associated Code).
Graph Neural Network-based Tracking as a Service Presented at Connecting the Dots 2023.
A Language Model for Particle Tracking Presented at Connecting the Dots 2023.
Hierarchical Graph Neural Networks for Particle Track Reconstruction Presented at ACAT 2022 (Associated Code ).
ATLAS ITk Track Reconstruction with a GNN-based pipeline Presented at Connecting the Dots 2022 (Associated Code).
Accelerating the Inference Time of Machine Learning-based Track Finding Pipeline Presented at ACAT 2021 ( Associated Code ).
Graph Neural Network for Large Radius Tracking Presented at ACAT 2021
Graph Neural Network for Object Reconstruction in Liquid Argon Time Projection Chambers Presented at CHEP 2021
Distributed Training of GNNs on HPCs Presented at the 4th Inter-experiment Machine Learning Workshop ( Associated Code ).
"Track Seeding and Labelling with Embedded-space Graph Neural Networks". Presented at Connecting the Dots 2020 - ( Associated Code ).
"Graph Neural Networks for Particle Reconstruction in High Energy Physics Detectors". Presented at NeurIPS 2019 Workshop "Machine Learning and the Physical Sciences" - (NeurIPS Poster) ( Associated Code ).

Full-length tutorial on Tracking with Graph Neural Networks (Sep 2023, Heidelberg) Part 1 - Part 2
Graph Neural Networks for High Luminosity Track Reconstruction (CERN EP-IT Data science seminar).
Graph Neural Networks for Reconstruction in DUNE (presented at the Dec 4th CLARIPHY topical meeting).
Tracking with GNNs (in-depth code walk-through at the 4th Inter-experiment Machine Learning Workshop) (colab notebook) ( Associated Code ).
Graph Neural Networks for Particle Tracking (A non-specialist introduction to Exa.TrkX tracking models).

reports, publications & presentations

project co-PI's

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