A Transparent and Efficient Extension of IceT for Parallel Compositing on Non-Convex Volume Domain Decompositions
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
The IceT library is widely used for parallel compositing but does not support non-convex volume domain decompositions. We provide a backward-compatible extension of IceT to handle non-convex domain decompositions of volume data. These are frequently produced in numerical simulations, but it is challenging to render them in parallel due to the non-commutativity of alpha compositing. We enable parallel volume rendering of non-convex domains in IceT by extending its parallel compositing to layered images. Our code follows an embedded design, extending and generalizing IceT's internal functions for image compression, splitting, compositing, and decompression to efficiently handle layered images, while maintaining the existing functionality and API. We perform scalability tests and provide our implementation open-source in a public repository, with in-line documentation and integration tests.
Description
CCS Concepts: Computing methodologies → Distributed algorithms; Rendering; Human-centered computing → Visualization techniques
@inproceedings{10.2312:pgv.20251151,
booktitle = {Eurographics Symposium on Parallel Graphics and Visualization},
editor = {Reina, Guido and Rizzi, Silvio and Gueunet, Charles},
title = {{A Transparent and Efficient Extension of IceT for Parallel Compositing on Non-Convex Volume Domain Decompositions}},
author = {Hempel, Paul and Gupta, Aryaman and Sbalzarini, Ivo F. and Gumhold, Stefan},
year = {2025},
publisher = {The Eurographics Association},
ISSN = {1727-348X},
ISBN = {978-3-03868-274-5},
DOI = {10.2312/pgv.20251151}
}