About
**Project Description**:
This project targets the deployment of real-time anomaly detection algorithms on FPGA devices to identify physics phenomena that may evade standard, model-driven trigger selections in the CMS experiment. The central objective is the implementation of a ML architecture based on a transformer model, adapted for ultra-low-latency inference in hardware.
This project investigates whether modern heterogeneous hardware platforms, specifically AMD Adaptive Compute Acceleration Platforms (ACAPs), can meet our strict latency, throughput, and determinism requirements. These devices integrate programmable logic, processors, and Adaptive Intelligence (AI) Engines, offering a promising path toward scalable, real-time ML-based triggering and scouting solutions for CMS and future experiments.
**Supervisor**: Elias Leutgeb Thomas Owen James
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The talk
Credits and licence
- Institution
- CERN
- Speaker
- Eliot Mario Abramo
- Year
- 2026
- Language
- English
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Teens profiles and older, judged from what the source says about it. How courses are placed