Shell: Accelerating Ray Tracing on GPU

Ray tracing is a fundamental process in many areas including computer graphics and medical applications. Different hierarchical acceleration structures for ray tracing have been developed. Such ray tracing approaches executed on advanced many-core processors such as GPU, however, turns out to be memory bounded due to their frequent search operations in the hierarchical structures. This paper proposes a novel acceleration approach (called Shell) aiming to tackle the mismatch between the ray tracing behaviors and the GPU memory features. The approach can work with any common spatial hierarchical (e.g., Kd-trees) representation of a ray tracing scene. It organizes the information of adjacent regions into memory chunks which can be read by only one memory transaction in GPU, and guarantees the minimum number of memory transactions for each ray traversal. Performance evaluations of the Shell approach based on real medical images show that it is 4X to 7.8X faster than the existing most advanced Kd-tree based ray tracing approach on GPU. The performance gain may offer significant improvements for other GPU based algorithms that heavily depend on ray tracing, such as interactive rendering and radiation dose calculation.