基于gpu的并行光线追踪照明算法数据结构

D. Barboza, E. Clua
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引用次数: 6

摘要

光线追踪是一种广泛使用的技术,用于生成具有高保真度和真实感的计算机图像。然而,该技术的成本非常高,主要是因为该算法需要进行交叉计算。尽管如此,光线追踪仍然是一种高度并行化的算法,因为单个光线的计算是独立于其他光线的。这样,在GPU上实现光线追踪是一个自然的过程。数据结构可以用来减少光线追踪算法的处理负荷,减少交集计算的次数。在最近的工作中,这些结构被移植到GPU上,因此它们可以用来加速各种并行算法。在这项工作中,我们提出了一种使用八叉树作为加速结构的GPU光线跟踪实现。算法的每一步都在GPU上并行运行,从而消除了GPU和CPU之间的通信瓶颈。通过比较两种不同的方法,本工作还提出了在GPU上表示八叉树的最佳方法的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GPU-Based Data Structure for a Parallel Ray Tracing Illumination Algorithm
Ray tracing is a largely employed technique for generating computer images with high fidelity and realism. However, this technique is very costly, mainly because of the intersection calculations made by the algorithm. Still, ray tracing is a highly parallelizable algorithm, since the calculations for a single light ray are independent from the others. This way, the implementation of the ray tracing on the GPU is a natural process. Data structures can be employed for reducing the processing load of the ray tracing algorithm, minimizing the number of intersection calculations. In recent works, these structures are being ported to the GPU, so they can be used to accelerate various parallel algorithms. In this work, we proposed a GPU ray tracing implementation using an octree as acceleration structure. Every single step of the algorithm runs in parallel on the GPU, so the communication bottleneck between the GPU and the CPU is eliminated. This work also proposes the study of which is the best way to represent the octree on the GPU, by comparing two different approaches.
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