PulseDL-II: A System-on-Chip Neural Network Accelerator for Timing and Energy Extraction of Nuclear Detector Signals. (arXiv:2209.00884v1 [physics.ins-det])

Front-end electronics equipped with high-speed digitizers are being used and
proposed for future nuclear detectors. Recent literature reveals that deep
learning models, especially one-dimensional convolutional neural networks, are
promising when dealing with digital signals from nuclear detectors. Simulations
and experiments demonstrate the satisfactory accuracy and additional benefits
of neural networks in this area. However, specific hardware accelerating such
models for online operations still needs to be studied. In this work, we
introduce PulseDL-II, a system-on-chip (SoC) specially designed for
applications …

arxiv chip energy extraction network neural network physics system-on-chip