TrackGNN: A Highly Parallelized and FIFO-Balanced GNN Accelerator for Track Reconstruction on FPGAs

This paper proposes TrackGNN, a highly parallelized GNN accelerator designed for efficient track reconstruction in high energy physics. We introduce a FIFO-balanced architecture optimized for FPGA implementation, achieving state-of-the-art performance.

Keywords: GNN, FPGA, Track Reconstruction, High Energy Physics
Read the paper

Recommended citation: S. Li, H. Zhang, R. Chen, C. Hao. "TrackGNN: A Highly Parallelized and FIFO-Balanced GNN Accelerator for Track Reconstruction on FPGAs." 33rd IEEE FCCM, 2025.
Download Paper