23th Meeting "Residency Octree - A Hybrid Approach for Scalable Web-Based Multi-Volume Rendering"
Please join us Friday, 12/08/2023 11AM ET for a talk titled “Residency Octree: A Hybrid Approach for Scalable Web-Based Multi-Volume Rendering”. We present a hybrid multi-volume rendering approach based on a novel Residency Octree that combines the advantages of out-of-core volume rendering using page tables with those of standard octrees. Octree approaches work by performing hierarchical tree traversal. However, in octree volume rendering, tree traversal and the selection of data resolution are intrinsically coupled. This makes fine-grained empty-space skipping costly. Page tables, on the other hand, allow access to any cached brick from any resolution. However, they do not offer a clear and efficient strategy for substituting missing high-resolution data with lower-resolution data. We enable flexible mixed-resolution out-of-core multi-volume rendering by decoupling the cache residency of multi-resolution data from a resolution-independent spatial subdivision determined by the tree. Instead of one-to-one node-to-brick correspondences, each residency octree node is mapped to a set of bricks from different resolution levels. This makes it possible to efficiently and adaptively choose and mix resolutions, adapt sampling rates, and compensate for cache misses. At the same time, residency octrees support fine-grained empty-space skipping, independent of the data subdivision used for caching. Finally, to facilitate collaboration and outreach, and to eliminate local data storage, our implementation is a web-based, pure client-side renderer using WebGPU and WebAssembly. Our method is faster than prior approaches and efficient for many data channels with a flexible and adaptive choice of data resolution.
Presenters: Lukas Herzberger hold a Master in Computer Science from the University of Vienna. He was a visiting researcher in 22/23 at the Laboratory of Pharmacology at Harvard Medical School in collaboration with the Visual Computing Group at Harvard SEAS.
https://vcg.seas.harvard.edu/publications/residency-octree/paper