A 22nm 3.5TOPS/W Flexible Micro-Robotic Vision SoC with 2MB eMRAM for Fully-on-Chip Intelligence

Abstract

We present a highly flexible micro-robotic vision SoC featuring a hybrid Processing Element (PE) for efficient processing of both Convolutional Neural Network (CNN) and non-CNN vision tasks with 2MB embedded MRAM for retentive fully-on-chip weight storage. Fabricated in 22nm, the design achieves 0.22nJ/pix for Harris corner detection (a non-CNN vision task) and 3.5TOPS/W (INT16) for CNN, a 60% efficiency improvement over state-of-the-art NVM-based NN ASICs.