CERN Burns Tiny AI Models into Silicon for Real-Time LHC Collision Filtering

CERN Uses Custom AI Chips for LHC Data Filtering

CERN is deploying AI inference models directly compiled into FPGA/ASIC hardware for real-time data filtering at the Large Hadron Collider, enabling nanosecond-scale classification decisions on 1 billion collisions per second.

The Approach

• Tiny models with just thousands of parameters, quantized to fixed-point arithmetic
• Pipeline-parallel filtering stages on radiation-hardened hardware
• Eliminates CPU software bottleneck in the microsecond-scale filtering requirement

Broader Impact

This edge-AI deployment at extreme scale demonstrates techniques applicable to autonomous vehicles, telecommunications, space hardware, and high-frequency trading systems where latency must be measured in nanoseconds.