CPU Ray Tracing Large Particle Data with Balanced P-k-d Trees

被引:0
|
作者
Wald, Ingo [1 ]
Knoll, Aaron [2 ]
Johnson, Gregory P. [1 ]
Usher, Will [2 ]
Pascucci, Valerio [2 ]
Papka, Michael E. [3 ]
机构
[1] Intel Corp, Santa Clara, CA 95051 USA
[2] Univ Utah, Inst Sci, Salt Lake City, UT 84112 USA
[3] Northern Illinois Univ, Argonne Natl Lab, De Kalb, IL USA
来源
2015 IEEE SCIENTIFIC VISUALIZATION CONFERENCE (SCIVIS) | 2015年
关键词
Ray tracing; Visualization; Particle Data; k-d Trees; VISUALIZATION;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
We present a novel approach to rendering large particle data sets from molecular dynamics, astrophysics and other sources. We employ a new data structure adapted from the original balanced k-d tree, which allows for representation of data with trivial or no overhead. In the OSPRay visualization framework, we have developed an efficient CPU algorithm for traversing, classifying and ray tracing these data. Our approach is able to render up to billions of particles on a typical workstation, purely on the CPU, without any approximations or level-of-detail techniques, and optionally with attribute-based color mapping, dynamic range query, and advanced lighting models such as ambient occlusion and path tracing.
引用
收藏
页码:57 / 64
页数:8
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