학술논문

A Memory Efficient Encoding for Ray Tracing Large Unstructured Data
Document Type
Periodical
Source
IEEE Transactions on Visualization and Computer Graphics IEEE Trans. Visual. Comput. Graphics Visualization and Computer Graphics, IEEE Transactions on. 28(1):583-592 Jan, 2022
Subject
Computing and Processing
Bioengineering
Signal Processing and Analysis
Rendering (computer graphics)
Memory management
Encoding
Mars
NASA
Data structures
Computational modeling
Language
ISSN
1077-2626
1941-0506
2160-9306
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 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.