On-the-Fly Power-Aware Rendering

TL;DR

This paper introduces a real-time, power-aware rendering framework that dynamically selects optimal rendering configurations to maximize quality within power constraints, suitable for both desktop and mobile devices.

Contribution

It presents a novel runtime power prediction model and quality error estimation mechanism that enable dynamic, on-the-fly rendering configuration optimization without precomputations.

Findings

Achieves near-maximum quality with significant power savings.

Works effectively on both desktop and mobile platforms.

Handles dynamic scenes without precomputations.

Abstract

Power saving is a prevailing concern in desktop computers and, especially, in battery-powered devices such as mobile phones. This is generating a growing demand for power-aware graphics applications that can extend battery life, while preserving good quality. In this paper, we address this issue by presenting a real-time power-efficient rendering framework, able to dynamically select the rendering configuration with the best quality within a given power budget. Different from the current state of the art, our method does not require precomputation of the whole camera-view space, nor Pareto curves to explore the vast power-error space; as such, it can also handle dynamic scenes. Our algorithm is based on two key components: our novel power prediction model, and our runtime quality error estimation mechanism. These components allow us to search for the optimal rendering configuration at runtime, being transparent to the user. We demonstrate the performance of our framework on two different platforms: a desktop computer, and a mobile device. In both cases, we produce results close to the maximum quality, while achieving significant power savings.