ISCAS OpenIR
Memory-efficient single-pass GPU rendering of multifragment effects
Wang, Wencheng (1); Xie, Guofu (1)
2013
SourceIEEE Transactions on Visualization and Computer Graphics
ISSN10772626
Volume19Issue:8Pages:1307-1316
English AbstractRendering multifragment effects using graphics processing units (GPUs) is attractive for high speed. However, the efficiency is seriously compromised, because ordering fragments on GPUs is not easy and the GPU's memory may not be large enough to store the whole scene geometry. Hitherto, existing methods have been unsuitable for large models or have required many passes for data transmission from CPU to GPU, resulting in a bottleneck for speedup. This paper presents a stream method for accurate rendering of multifragment effects. It decomposes the model into parts and manages these in an efficient manner, guaranteeing that the parts can easily be ordered with respect to any viewpoint, and that each part can be rendered correctly on the GPU. Thus, we can transmit the model data part by part, and once a part has been loaded onto the GPU, we immediately render it and composite its result with the results of the processed parts. In this way, we need only a single pass for data access with a very low bounded memory requirement. Moreover, we treat parts in packs for further acceleration. Results show that our method is much faster than existing methods and can easily handle large models of any size. © 1995-2012 IEEE.; Rendering multifragment effects using graphics processing units (GPUs) is attractive for high speed. However, the efficiency is seriously compromised, because ordering fragments on GPUs is not easy and the GPU's memory may not be large enough to store the whole scene geometry. Hitherto, existing methods have been unsuitable for large models or have required many passes for data transmission from CPU to GPU, resulting in a bottleneck for speedup. This paper presents a stream method for accurate rendering of multifragment effects. It decomposes the model into parts and manages these in an efficient manner, guaranteeing that the parts can easily be ordered with respect to any viewpoint, and that each part can be rendered correctly on the GPU. Thus, we can transmit the model data part by part, and once a part has been loaded onto the GPU, we immediately render it and composite its result with the results of the processed parts. In this way, we need only a single pass for data access with a very low bounded memory requirement. Moreover, we treat parts in packs for further acceleration. Results show that our method is much faster than existing methods and can easily handle large models of any size. © 1995-2012 IEEE.
Indexed TypeSCI ; EI
KeywordMultifragment Effects Depth Ordering Fixed Amount Of Memory Large Models Accurate Rendering
Department(1) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, No. 4, South 4th Street, Zhongguancun, Haidian District, Beijing 100190, China; (2) University of Chinese Academy of Sciences, Beijing 100049, China
Language英语
WOS IDWOS:000320658600006
Citation statistics
Content Type期刊论文
URIhttp://ir.iscas.ac.cn/handle/311060/16696
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Wang, Wencheng ,Xie, Guofu . Memory-efficient single-pass GPU rendering of multifragment effects[J]. IEEE Transactions on Visualization and Computer Graphics,2013,19(8):1307-1316.
APA Wang, Wencheng ,&Xie, Guofu .(2013).Memory-efficient single-pass GPU rendering of multifragment effects.IEEE Transactions on Visualization and Computer Graphics,19(8),1307-1316.
MLA Wang, Wencheng ,et al."Memory-efficient single-pass GPU rendering of multifragment effects".IEEE Transactions on Visualization and Computer Graphics 19.8(2013):1307-1316.
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