Front-end electronics (FEEs) equipped with high-speed digitizers are being used and proposed for future nuclear detectors. Recent literature reveals that deep learning models, especially 1-D convolutional neural networks (NNs), are promising when dealing with digital signals from nuclear detectors. Simulations and experiments demonstrate the satisfactory accuracy and additional benefits of NNs in this area. However, specific hardware accelerating such models for online operations still needs to be studied. In this work, we introduce PulseDL-II,...
