FNAL: Ultrafast Neural Networks for On-Detector Edge Processing in Resource-Constrained Extreme Radiation Environment

Fermi National Accelerator Laboratory will demonstrate that a neural network (NN) autoencoder model can be implemented in a radiation-tolerant application-specific integrated circuit (ASIC) to perform lossy data compression alleviating the data transmission problem while preserving critical information of the detector energy profile.