Microsecond Inference: How TinyML Powers CERN's Real-Time Physics Filter

CERN's Large Hadron Collider generates petabytes of sensor data per second, yet must filter collision events in just 3–4 microseconds to determine what's worth keeping. While GPUs excel at throughput, their millisecond-scale latency makes them unsuitable for this extreme constraint. TinyML deployed on FPGAs through the open-source hls4ml tool achieves the microsecond-scale inference required, making neural networks essential infrastructure for modern particle physics at the scale of billions of interactions per second.