A 12-nm 0.62-1.61 mW Ultra-Low Power Digital CIM-based Deep-Learning System for End-to-End Always-on Vision

Abstract

This work proposes an ultra-low power DCIM-based DL system (DCIM-DLS) for end-to-end AoV with the power range from 0.62 to 1.61 mW (INT8, 2-15 fps). Compared to the prior art [3], the power consumption of DCIM-DLS can be reduced by 70.9% based on the following techniques: 1) an area and energy efficient DCIM that reduces compute RC loading by using pushed-rule 2p8T SRAM bitcell with folded kernels selector, 2) a DCIM-friendly dataflow strategy with dual accumulators that minimizes the DCIM power of weight update and avoids redundant data movement for power saving, and 3) a reconfigurable DCIM control scheme that supports mixed-precision to further reduce power consumption.