Revolutionizing Data Processing at CERN with Compact AI Models
In a groundbreaking approach, CERN is using ultra-small artificial intelligence models burned directly into silicon to tackle the immense data generated by the Large Hadron Collider (LHC). This method allows for real-time filtering of data, making split-second decisions on which collision events are worth preserving.
Key Highlights:
- The LHC generates approximately 40,000 exabytes of raw data annually.
- Only 0.02% of collision events are retained for further analysis.
- CERN’s AI models, compiled using HLS4ML, enable ultra-low latency inference in nanoseconds.
- The system employs field-programmable gate arrays (FPGAs) and custom application-specific integrated circuits (ASICs) for optimal performance.
Looking to the future, CERN is gearing up for the High-Luminosity LHC, anticipating a tenfold increase in data per collision, further driving the need for these innovative AI solutions.
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