Sort-first, distributed memory parallel visualization and rendering

E. W. Bethel, G. Humphreys, Brian E. Paul, J. D. Brederson
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引用次数: 42

Abstract

While commodity computing and graphics hardware has increased in capacity and dropped in cost, it is still quite difficult to make effective use of such systems for general-purpose parallel visualization and graphics. We describe the results of a recent project that provides a software infrastructure suitable for general-purpose use by parallel visualization and graphics applications. Our work combines and extends two technologies: chromium, a stream-oriented framework that implements the OpenGL programming interface; and OpenRM scene graph, a pipelined-parallel scene graph interface for graphics data management. Using this combination, we implement a sort-first, distributed memory, parallel volume rendering application. We describe the performance characteristics in terms of bandwidth requirements and highlight key algorithmic considerations needed to implement the sort-first system. We characterize system performance using a distributed memory parallel volume rendering application, and present performance gains realized by using scene specific knowledge to accelerate rendering by reducing network traffic. The contribution of this work is an exploration of general-purpose, sort-first architecture performance characteristics as applied to distributed memory, commodity hardware, along with a description of the algorithmic support needed to realize parallel, sort-first implementations.
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排序优先,分布式内存并行可视化和渲染
虽然商品计算和图形硬件的容量增加了,成本下降了,但是要有效地利用这些系统进行通用的并行可视化和图形化仍然相当困难。我们描述了最近一个项目的结果,该项目提供了一个软件基础设施,适合并行可视化和图形应用程序的通用用途。我们的工作结合并扩展了两种技术:chromium,一个实现OpenGL编程接口的面向流的框架;OpenRM场景图,一个用于图形数据管理的流水线并行场景图接口。使用这种组合,我们实现了一个排序优先、分布式内存、并行体渲染应用程序。我们描述了带宽需求方面的性能特征,并强调了实现排序优先系统所需的关键算法考虑因素。我们使用分布式内存并行体渲染应用程序来表征系统性能,并通过使用场景特定知识通过减少网络流量来加速渲染来实现性能提升。这项工作的贡献是对应用于分布式内存、商用硬件的通用、排序优先架构性能特征的探索,以及对实现并行、排序优先实现所需的算法支持的描述。
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