Hannah Kim, Celia Cintas, et al.
IJCAI 2023
We present a sort-first parallel system for out-of-core rendering of large models on cluster-based tiled displays. The system renders high-resolution images of large models at interactive frame rates using off-the-shelf PCs with small memory. Given a model, we use an out-of-core preprocessing algorithm to build an on-disk hierarchical representation for the model. At run time, each PC renders the image for a display tile, using an out-of-core rendering approach that employs multiple threads to overlap rendering, visibility computation, and disk operations. The system can operate in approximate mode for real-time rendering, or in conservative mode for rendering with guaranteed accuracy. Running our system in approximate mode on a cluster of 16 PCs each with 512 MB of main memory, we are able to render 12-megapixel images of a 13-million-triangle model with 99.3% of accuracy at 10.8 frames per second. Rendering such a large model at high resolutions and interactive frame rates would typically require expensive high-end graphics hardware. Our results show that a cluster of inexpensive PCs is an attractive alternative to those high-end systems. © 2002 Elsevier Science B.V. All rights reserved.
Hannah Kim, Celia Cintas, et al.
IJCAI 2023
Annina Riedhauser, Viacheslav Snigirev, et al.
CLEO 2023
Zahra Ashktorab, Djallel Bouneffouf, et al.
IJCAI 2025
Gaku Yamamoto, Hideki Tai, et al.
AAMAS 2008