Abstract

In recent years, applying the powerful computational resources delivered by modern GPUs to ray tracing has resulted in a number of ray tracing implementations that allow rendering of moderately sized scenes at interactive speeds. For non-static scenes, besides ray tracing performance, fast construction of acceleration data structures such as kd-trees is of primary concern. In this paper, we present a novel implementation for the ray tracing of both static and dynamic scenes. We first describe an optimized GPU-based ray tracing approach within the CUDA framework that does not explicitly make use of ray coherency or architectural specifics and is therefore simple to implement, while still exceeding performance of previously presented approaches. Optimal performance is achieved by empirically tuning the ray tracing kernel to the executing hardware. Furthermore, we describe a straightforward parallel approach for approximate quality kd-tree construction, aimed at multi-core CPUs. The resulting hybrid ray tracer is able to render fully dynamic scenes with hundreds of thousands of triangles at interactive speeds. We describe our implementation in detail and provide a performance analysis and comparison to prior work.

Citations