Conference Presentation (After Call)

FZJ-2025-04469

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png FPGA-Based Real-Time Waveform Classification and Reduction in Particle Detectors

Bekman, I. (Corresponding author)FZJ* ; Eguzo, C. V.FZJ*

2025

This record in other databases:  

Please use a persistent id in citations: doi:10.34734/FZJ-2025-04469

Abstract: The SHiP SBT self-triggered readout will process SiPM sum signals sampled at 800 MSPS and 12 bit resolution to extract calorimetric particle hit information. A waveform classification is being deployed on the readout FPGA to reduce the volume of transmitted data.The classification divides events into expected signal, expected noise or containing unexpected features applying different degrees of compression.In this study, we consider LUT-based neural-networks and address challenges of NN layout, footprint and performance. Preliminary planning indicates significant data reduction, easing constraints on infrastructure.

---

Contributing Institute(s):

1. Integrated Computing Architectures (PGI-4)

Research Program(s):

1. 5234 - Emerging NC Architectures (POF4-523) (POF4-523)

Appears in the scientific report 2025

---

Database coverage:

---