State-of-the-art in Large-Scale Volume Visualization Beyond Structured Data

Abstract
Volume data these days is usually massive in terms of its topology, multiple fields, or temporal component. With the gap between compute and memory performance widening, the memory subsystem becomes the primary bottleneck for scientific volume visualization. Simple, structured, regular representations are often infeasible because the buses and interconnects involved need to accommodate the data required for interactive rendering. In this state-of-the-art report, we review works focusing on largescale volume rendering beyond those typical structured and regular grid representations.We focus primarily on hierarchical and adaptive mesh refinement representations, unstructured meshes, and compressed representations that gained recent popularity. We review works that approach this kind of data using strategies such as out-of-core rendering, massive parallelism, and other strategies to cope with the sheer size of the ever-increasing volume of data produced by today's supercomputers and acquisition devices. We emphasize the data management side of large-scale volume rendering systems and also include a review of tools that support the various volume data types discussed.
Description

CCS Concepts: Computing methodologies -> Rendering; Volumetric models; Ray tracing; Graphics processors; Massively parallel algorithms; Distributed algorithms; Human-centered computing -> Visualization toolkits; Scientific visualization

        
@article{
10.1111:cgf.14857
, journal = {Computer Graphics Forum}, title = {{
State-of-the-art in Large-Scale Volume Visualization Beyond Structured Data
}}, author = {
Sarton, Jonathan
 and
Zellmann, Stefan
 and
Demirci, Serkan
 and
Güdükbay, Ugur
 and
Alexandre-Barff, Welcome
 and
Lucas, Laurent
 and
Dischler, Jean-Michel
 and
Wesner, Stefan
 and
Wald, Ingo
}, year = {
2023
}, publisher = {
The Eurographics Association and John Wiley & Sons Ltd.
}, ISSN = {
1467-8659
}, DOI = {
10.1111/cgf.14857
} }
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