A Memory Efficient Encoding for Ray Tracing Large Unstructured Data

A Memory Efficient Encoding for Ray Tracing Large Unstructured Data

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...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 28(2022), 1 vom: 29. Jan., Seite 583-592
1. Verfasser: Wald, Ingo (VerfasserIn)
Weitere Verfasser: Morrical, Nate, Zellmann, Stefan
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2022
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article
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520 |a 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 
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