A Memory Efficient Encoding for Ray Tracing Large Unstructured Data

Ingo Wald, Nate Morrical, Stefan Zellmann

View presentation: 2021-10-28T16:00:00Z GMT-0600 Change your timezone on the schedule page
2021-10-28T16:00:00Z
Exemplar figure, but none was provided by the authors
Abstract

In theory, efficient and high-quality rendering of unstructured data should greatly benefit from modern GPUs, but in practice, GPUs are often limited by the large amount of memory that large meshes require for element representation and for sample reconstruction acceleration structures. We describe a memory-optimized encoding for large unstructured meshes that efficiently encodes both the unstructured mesh and corresponding sample reconstruction acceleration structure, while still allowing for fast random-access sampling as required for rendering. We demonstrate that for large data our encoding is more efficient than OSPRay’s and allows for rendering even the 2.9 billion element Mars Lander on a single off-the-shelf GPU--and the largest 6.3 billion version on a pair of such GPUs.