Power, Performance, and Image Quality Tradeoffs in Foveated Rendering
Rahul Singh, Muhammad Huzaifa, Jeffrey Liu, Anjul Patney, Hashim Sharif, Yifan Zhao, Sarita V. Adve
Abstract
Extended reality (XR) devices, including augmented, virtual, and mixed reality, provide a deeply immersive experience. However, practical limitations like weight, heat, and comfort put extreme constraints on the performance, power consumption, and image quality of such systems. In this paper, we study how these constraints form the tradeoff between Fixed Foveated Rendering (FFR), Gaze-Tracked Foveated Rendering (TFR), and conventional, non-foveated rendering. While existing papers have often studied these methods, we provide the first comprehensive study of their relative feasibility in practical systems with limited battery life and computational budget. We show that TFR with the added cost of the gaze-tracker can often be more expensive than FFR. Thus, we co-design a gaze-tracked foveated renderer considering its benefits in computation, power efficiency, and tradeoffs in image quality. We describe principled approximations for eye tracking which provide up to a 9x speedup in runtime performance with approximately a 20x improvement in energy efficiency when run on a mobile GPU. In isolation, these approximations appear to significantly degrade the gaze quality, but appropriate compensation in the visual pipeline can mitigate the loss. Overall, we show that with a highly optimized gaze-tracker, TFR is feasible compared to FFR, resulting in up to 1.25x faster frame times while also reducing total energy consumption by over 40%.