对象并行渲染的像素合并:一种分布式窥探算法

M. Cox, P. Hanrahan
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引用次数: 28

摘要

在多处理器渲染的纯对象并行方法中,每个处理器被分配责任来渲染图形数据库的一个子集。渲染完成后,来自处理器的像素必须合并并进行全局z缓冲。在任意多处理器互连网络上,像素合并的直接算法需要d/sup -/每帧的总网络带宽,其中d/sup -/是场景的深度复杂度,A是屏幕或窗口的面积。该算法被久保田太平洋Denali所使用,似乎也被埃文斯和萨瑟兰自由系列所使用。另一种算法,PixelFlow算法,每帧需要nA网络带宽,其中n是处理器的数量。但是合并在PixelFlow中是流水线化的,所以每个网络链接每帧只能支持A带宽。然而,该算法需要一个单独的专用网络来进行像素合并。本文提出并分析了一种使用网络广播的期望情况日志(d/sup -/)像素合并算法,并讨论了该算法在共享内存总线体系结构中的适用性。
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Pixel merging for object-parallel rendering: A distributed snooping algorithm
In the purely object-parallel approach to multiprocessor rendering, each processor is assigned responsibility to render a subset of the graphics database. When rendering is complete, pixels from the processors must be merged and globally z-buffered. On an arbitrary multiprocessor interconnection network, the straightforward algorithm for pixel merging requires d/sup -/A total network bandwidth per frame, where d/sup -/ is the depth complexity of the scene and A is the area of the screen or window. This algorithm is used by the Kubota Pacific Denali and appears to be used by the Evans and Sutherland Freedom series. An alternative algorithm, the PixelFlow algorithm, requires nA network bandwidth per frame, where n is the number of processors. But the merging is pipelined in PixelFlow so that each network link must only support A bandwidth per frame. However, that algorithm requires a separate special-purpose network for pixel merging. In this paper we present and analyze an expected-case log (d/sup -/)A algorithm for pixel merging that uses network broadcast, and we discuss the algorithm's applicability to shared-memory bus architectures.
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