GPU-based out-of-core many-lights rendering

Abstract

In this paper, we present a GPU-based out-of-core rendering approach under the many-lights rendering framework. Many-lights rendering is an efficient and scalable rendering framework for a large number of lights. But when the data sizes of lights and geometry are both beyond the in-core memory storage size, the data management of these two out-of-core data becomes critical and challenging. In our approach, we formulate such a data management as a graph traversal optimization problem that first builds out-of-core lights and geometry data into a graph, and then guides shading computations by finding a shortest path to visit all vertices in the graph. Based on the proposed data management, we develop a GPU-based out-of-GPU-core rendering algorithm that manages data between the CPU host memory and the GPU device memory. Two main steps are taken in the algorithm: the out-of-core data preparation to pack data into optimal data layouts for the many-lights rendering, and the out-of-core shading using graph-based data management. We demonstrate our algorithm on scenes with out-of-core detailed geometry and out-of-core lights. Results show that our approach generates complex global illumination effects with increased data access coherence and has one order of magnitude performance gain over the CPU-based approach.

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Index Terms

• Computing methodologies

  • Artificial intelligence

    • Computer vision

      • Image and video acquisition

        • 3D imaging

  • Computer graphics

    • Animation