Decoupled sampling for graphics pipelines
Decoupled sampling for graphics pipelines
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DOI：
10.1145/1966394.1966396
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发表时间：
2011-05
期刊：
影响因子：
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通讯作者：
Jonathan Ragan-Kelley;J. Lehtinen;Jiawen Chen;M. Doggett;F. Durand
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文献类型：
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作者：
Jonathan Ragan-Kelley;J. Lehtinen;Jiawen Chen;M. Doggett;F. Durand
我们提出了一种通用的方法来解耦阴影可见性采样在图形管道，我们称之为解耦采样。解耦采样使得能够以降低的着色成本实现运动和散焦模糊的随机超分辨率，以及可控或自适应的着色速率，其权衡着色质量以获得性能。它可以被认为是多采样抗锯齿（MSAA）的泛化，以支持从可见性到着色采样的复杂和动态映射，如运动和散焦模糊以及自适应着色所引入的。它的工作原理是定义一个从可见性到着色样本的多对一哈希，并使用一个缓冲区来记忆着色样本，并利用可见性样本之间的重用。解耦采样受到Reyes渲染架构的启发，但与传统的图形管道一样，它会对片段而不是微多边形顶点进行着色，从而将着色与几何采样率解耦。与Reyes不同的是，解耦采样仅在精确计算可见性后对片段进行着色，从而减少过度着色。我们提出了两个现代图形管道的扩展，以支持解耦采样：GPU风格的排序最后片段架构，和Larrabee风格的排序中间管道。我们研究了解耦采样和模糊的架构影响，并通过仪表功能模拟器获得真实的应用程序的端到端性能估计。我们展示了高质量的运动和散焦模糊，以及可变和自适应着色率。
We propose a generalized approach to decoupling shading from visibility sampling in graphics pipelines, which we call decoupled sampling. Decoupled sampling enables stochastic supersampling of motion and defocus blur at reduced shading cost, as well as controllable or adaptive shading rates which trade off shading quality for performance. It can be thought of as a generalization of multisample antialiasing (MSAA) to support complex and dynamic mappings from visibility to shading samples, as introduced by motion and defocus blur and adaptive shading. It works by defining a many-to-one hash from visibility to shading samples, and using a buffer to memoize shading samples and exploit reuse across visibility samples. Decoupled sampling is inspired by the Reyes rendering architecture, but like traditional graphics pipelines, it shades fragments rather than micropolygon vertices, decoupling shading from the geometry sampling rate. Also unlike Reyes, decoupled sampling only shades fragments after precise computation of visibility, reducing overshading. We present extensions of two modern graphics pipelines to support decoupled sampling: a GPU-style sort-last fragment architecture, and a Larrabee-style sort-middle pipeline. We study the architectural implications of decoupled sampling and blur, and derive end-to-end performance estimates on real applications through an instrumented functional simulator. We demonstrate high-quality motion and defocus blur, as well as variable and adaptive shading rates.