Stream compaction for deferred shading
Stream compaction for deferred shading
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用于延迟着色的流压缩
DOI：
10.1145/1572769.1572797
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
J. Hart
中科院分区：
文献类型：
--
作者：
Jared Hoberock;Victor Lu;Yuntao Jia;J. Hart
GPU在阴影时利用SIMD效率，因为它一次擦拭三角形，在其所有片段上运行相同的着色器。射线追踪牺牲这种着色器的连贯性，结果是SIMD单位通常必须同时运行不同的着色器，从而导致序列化。我们研究了这个问题，并定义了一种称为异质效率的新措施，以测量射线跟踪应用中不同复杂性的多个着色器之间的SIMD差异。我们设计了七种不同的算法，以将着色器安排到SIMD处理器上，以避免发散。除了简单的阴影场景外，我们还表明了分类着色器以更好的整体阴影性能付出的费用。
The GPU leverages SIMD efficiency when shading because it rasterizes a triangle at a time, running the same shader on all of its fragments. Ray tracing sacrifices this shader coherence, and the result is that SIMD units often must run different shaders simultaneously resulting in serialization. We study this problem and define a new measure called heterogeneous efficiency to measure SIMD divergence among multiple shaders of different complexities in a ray tracing application. We devise seven different algorithms for scheduling shaders onto SIMD processors to avoid divergence. In all but simply shaded scenes, we show the expense of sorting shaders pays off with better overall shading performance.