Abstract
Many instruments used in high-energy particle physics observations, e.g., gamma-ray telescopes, use FPGAs for front-end signal processing of raw sensor data. The use of high-level synthesis (HLS) to express the signal processing algorithms has the potential to significantly reduce development time for new instruments of this type. We describe our experience with one of the computational stages in the signal processing pipeline, island detection, exploring its implementation across multiple configurations: 1D versus 2D islands, and 4-way versus 8-way connected-component labeling (CCL) in the 2D configuration. We report resource usage and performance for both configurations of 2D island detection, including the required optimizations necessary for HLS to be effective. Results indicate that our implementation can perform 4-way CCL on 15k images per second even for 43 x 43 pixel arrays.
Recommended Citation
N. Song et al., "Connected-Component Labeling Using HLS For High-Energy Particle Physics Instruments," Proceedings of 2025 Workshops of the International Conference on High Performance Computing Network Storage and Analysis Sc 2025 Workshops, pp. 642 - 650, Association for Computing Machinery (ACM), Nov 2025.
The definitive version is available at https://doi.org/10.1145/3731599.3767413
Meeting Name
SC '25 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis
Department(s)
Computer Science
Publication Status
Open Access
Keywords and Phrases
CCL; high-level synthesis; particle physics
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2026 The Authors, All rights reserved.
Creative Commons Licensing

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.
Publication Date
15 Nov 2025
Included in
Databases and Information Systems Commons, Other Computer Sciences Commons, Systems Architecture Commons

Comments
University of Washington, Grant 80NSSC21K1741