@article{23377fd81d094c2f83bd135253c99afa,
title = "Hardware-assisted visibility sorting for unstructured volume rendering",
abstract = "Harvesting the power of modern graphics hardware to solve the complex problem of real-time rendering of large unstructured meshes is a major research goal in the volume visualization community. While, for regular grids, texture-based techniques are well-suited for current GPUs, the steps necessary for rendering unstructured meshes are not so easily mapped to current hardware. We propose a novel volume rendering technique that simplifies the CPU-based processing and shifts much of the sorting burden to the GPU, where it can be performed more efficiently. Our hardware-assisted visibility sorting algorithm is a hybrid technique that operates in both object-space and Image-space. In object-space, the algorithm performs a partial sort of the 3D primitives In preparation for rasterization. The goal of the partial sort is to create a list of primitives that generate fragments in nearly sorted order. In image-space, the fragment stream is incrementally sorted using a fixed-depth sorting network. In our algorithm, the object-space work is performed by the CPU and the fragment-level sorting is done completely on the CPU. A prototype implementation of the algorithm demonstrates that the fragment-level sorting achieves rendering rates of between one and six million tetrahedral cells per second on an ATI Radeon 9800.",
keywords = "Graphics processors, Visibility sorting, Volume visualization",
author = "Callahan, {Steven P.} and Milan Ikits and Comba, {Jo{\~a}o L D} and Silva, {Cl{\'a}udi{\'o} T.}",
note = "Funding Information: The authors thank Joe Kniss for suggesting that the k-buffer could be implemented efficiently on ATI hardware. They thank Ricardo Farias for the ZSWEEP code and the insightful discussions that helped shape many ideas presented in this paper. Carlos Scheidegger and Huy Vo provided invaluable code contributions. In particular, Vo wrote the fast radix sort used in their system. They thank F{\'a}bio Bernardon for the use of his HW Ray Caster code. The Teem toolkit [44] proved very useful for processing the data sets and results. They thank Mark Segal from ATI for the donated hardware and his prompt answers to their questions. They are grateful to Patricia Crossno, Shachar Fleishman, Nelson Max, and Peter Shirley for helpful suggestions and criticism. The authors also acknowledge Bruce Hopenfeld and Robert MacLeod (University of Utah) for the heart data set, Bruno Notrosso (Electricite de France) for the spx data set, Hung and Buning (NASA) for the blunt fin data set, and Neely and Batina (NASA) for the fighter data set. Steven P. Callahan is supported by the US Department of Energy (DOE) under the VIEWS program. Milan Ikits is supported by the US National Science Foundation (NSF) grant ACI-0078063 and the DOE Advanced Visualization Technology Center. Cl{\'a}udio T. Silva is partially supported by the DOE under the VIEWS program and the MICS office, the NSF under grants CCF-0401498, EIA-0323604, and OISE-0405402, and a University of Utah Seed Grant. The work of Jo{\~a}o L.D. Comba is supported by a CNPq grant 540414/01-8 and FAPERGS grant 01/0547.3.",
year = "2005",
month = may,
doi = "10.1109/TVCG.2005.46",
language = "English (US)",
volume = "11",
pages = "285--295",
journal = "IEEE Transactions on Visualization and Computer Graphics",
issn = "1077-2626",
publisher = "IEEE Computer Society",
number = "3",
}