A Deep Neural Network Training Architecture With Inference-Aware Heterogeneous Data-Type

As deep learning applications often encounter accuracy degradation due to the distorted inputs from a variety of environmental conditions, training with personal data has become essential for the edge devices. Hence, ‘training on edge’ by supporting a trainable deep learning accelerator has been actively studied. Nevertheless, previous research does not consider the fundamental datapath for traini...