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Title:
Memory-efficient single-pass GPU rendering of multifragment effects
Author: Wang, Wencheng (1) ; Xie, Guofu (1)
Keyword: Multifragment effects ; depth ordering ; fixed amount of memory ; large models ; accurate rendering
Source: IEEE Transactions on Visualization and Computer Graphics
Issued Date: 2013
Volume: 19, Issue:8, Pages:1307-1316
Indexed Type: SCI ; EI
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
Abstract: 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.
English Abstract: 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.
Language: 英语
WOS ID: WOS:000320658600006
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Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/16696
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Wang, Wencheng ,Xie, Guofu . Memory-efficient single-pass GPU rendering of multifragment effects[J]. IEEE Transactions on Visualization and Computer Graphics,2013-01-01,19(8):1307-1316.
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