A Dynamic Execution Neural Network Processor for Fine-Grained Mixed-Precision Mo

Abstract

As neural network (NN) training cost red has been growing exponentially over the past decade, developing high-speed and energy-efficient training methods has become an urgent task. Fine-grained mixed-precision low-bit training is the most promising way for high-efficiency training, but it needs dedicated processor designs to overcome the overhead in control, storage, and I/O and remove the power bottleneck in floating-point (FP) units. This article presents a dynamic execution NN processor suppo