重新构建用于生产的时空重采样

Chris Wyman, Alexey Panteleev
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引用次数: 13

摘要

Bitterli等人最近的研究[BWP* 20]引入了一种实时多光算法,通过加权水库采样迭代地应用重采样重要性采样,从数百万盏灯中绘制动态直接照明。虽然在实时中实现了新的照明复杂性水平,但总成本仍然超出了即使是对计算要求最高的游戏的预算。我们介绍了在生产这种方法的同时开发的关键算法改进,这些改进共同降低了高达7倍的照明成本,显着提高了内存一致性,缩小了所需的光线预算,提高了渲染质量,并暴露了能够以交易质量换取性能的参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rearchitecting spatiotemporal resampling for production
Recent work by Bitterli et al. [BWP* 20] introduced a real-time, many-light algorithm for rendering dynamic direct illumination from millions of lights by iteratively applying resampled importance sampling using weighted reservoir sampling. While enabling new levels of lighting complexity in real-time, the total cost remained beyond the budgets of even the most computationally demanding games. We introduce key algorithmic improvements developed while productizing this method that collectively reduce lighting costs by up to 7X, dramatically improve memory coherence, shrink the required ray budget, increase rendering quality, and expose parameters that enable trading quality for performance.
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