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Item Runtime Shader Simplification via Instant Search in Reduced Optimization Space(The Eurographics Association and John Wiley & Sons Ltd., 2018) Yuan, Yazhen; Wang, Rui; Hu, Tianlei; Bao, Hujun; Jakob, Wenzel and Hachisuka, ToshiyaTraditional automatic shader simplification simplifies shaders in an offline process, which is typically carried out in a contextoblivious manner or with the use of some example contexts, e.g., certain hardware platforms, scenes, and uniform parameters, etc. As a result, these pre-simplified shaders may fail at adapting to runtime changes of the rendering context that were not considered in the simplification process. In this paper, we propose a new automatic shader simplification technique, which explores two key aspects of a runtime simplification framework: the optimization space and the instant search for optimal simplified shaders with runtime context. The proposed technique still requires a preprocess stage to process the original shader. However, instead of directly computing optimal simplified shaders, the proposed preprocess generates a reduced shader optimization space. In particular, two heuristic estimates of the quality and performance of simplified shaders are presented to group similar variants into representative ones, which serve as basic graph nodes of the simplification dependency graph (SDG), a new representation of the optimization space. At the runtime simplification stage, a parallel discrete optimization algorithm is employed to instantly search in the SDG for optimal simplified shaders. New data-driven cost models are proposed to predict the runtime quality and performance of simplified shaders on the basis of data collected during runtime. Results show that the selected simplifications of complex shaders achieve 1.6 to 2.5 times speedup and still retain high rendering quality.Item On-the-Fly Power-Aware Rendering(The Eurographics Association and John Wiley & Sons Ltd., 2018) Zhang, Yunjin; OrtÃn, Marta; Arellano, Victor; Wang, Rui; Gutierrez, Diego; Bao, Hujun; Jakob, Wenzel and Hachisuka, ToshiyaPower 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.