面向集群的分布式实时渲染的图像层分解

Thu D. Nguyen, J. Zahorjan
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引用次数: 3

摘要

我们提出了一种新的工作划分技术,图像层分解(ILD),专门设计用于支持商品集群上的分布式实时渲染。对于我们的目标环境,ILD比以前的分区算法有几个优点,包括它与硬件图形加速器的使用的兼容性,从场景复杂性中解耦通信带宽需求,以及随着系统大小的增加而减少通信带宽的增长。此外,ILD试图优化(交互式应用程序的)帧序列的呈现,而不是仅仅优化单个帧的呈现。我们使用从VRML查看器获取的跟踪来模拟ILD。我们的结果表明,ILD可以很好地工作到中等大小的集群,并且优于sort-last(一种常见的分区方法),因为它的通信带宽要求更小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image layer decomposition for distributed real-time rendering on clusters
We propose a novel work partitioning technique, image layer decomposition (ILD), designed specifically to support distributed real-time rendering on commodity clusters. ILD has several advantages over previous partitioning algorithms for our targeted environment, including its compatibility with the use of hardware graphics accelerators, decoupling of communication bandwidth requirement from scene complexity, and reduced communication bandwidth growth as the system size increases. Furthermore, ILD tries to optimize the rendering of a sequence of frames (of an interactive application) instead of only individual frames. We simulate ILD using traces taken from a VRML viewer Our results show that ILD can be expected to work well up to moderately sized clusters and to outperform sort-last, a common partitioning approach, because of its smaller communication bandwidth requirement.
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