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Augmented Reality/Virtual Reality (AR/VR) glasses are widely foreseen as thenext generation computing platform. AR/VR glasses are a complex "system ofsystems" which must satisfy stringent form factor, computing-, power- andthermal- requirements. In this paper, we will show that a novel distributedon-sensor compute architecture, coupled with new semiconductor technologies(such as dense 3D-IC interconnects and Spin-Transfer Torque Magneto RandomAccess Memory, STT-MRAM) and, most importantly, a full hardware-softwareco-optimization are the solutions to achieve attractive and socially acceptableAR/VR glasses. To this end, we developed a semi-analytical simulation frameworkto estimate the power consumption of novel AR/VR distributed on-sensorcomputing architectures. The model allows the optimization of the maintechnological features of the system modules, as well as the computer-visionalgorithm partition strategy across the distributed compute architecture. Weshow that, in the case of the compute-intensive machine learning based HandTracking algorithm, the distributed on-sensor compute architecture can reducethe system power consumption compared to a centralized system, with theadditional benefits in terms of latency and privacy.

Distributed On-Sensor Compute System for AR/VR Devices: A Semi-Analytical Simulation Framework for Power Estimation