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A GPU‐based Approach for Massive Model Rendering with Frame‐to‐Frame Coherence
Author(s) -
Peng Chao,
Cao Yong
Publication year - 2012
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2012.03018.x
Subject(s) - computer science , rendering (computer graphics) , parallel rendering , software rendering , real time rendering , tiled rendering , computer graphics (images) , alternate frame rendering , 3d rendering , parallel computing , texture memory , frame rate , cuda , graphics , 3d computer graphics , artificial intelligence
Rendering massive 3D models in real‐time has long been recognized as a very challenging problem because of the limited computational power and memory space available in a workstation. Most existing rendering techniques, especially level of detail (LOD) processing, have suffered from their sequential execution natures. We present a GPU‐based approach which enables interactive rendering of large 3D models with hundreds of millions of triangles. Our work contributes to the massive rendering research in two ways. First, we present a simple and efficient mesh simplification algorithm towards GPU architecture. Second, we propose a novel GPU out‐of‐core approach that adopts a frame‐to‐frame coherence scheme in order to minimize the high communication cost between CPU and GPU. Our results show that the parallel algorithm of mesh simplification and the GPU out‐of‐core approach significantly improve the overall rendering performance.