A parallel image generation algorithm based on photon map partitioning
A parallel image generation algorithm based on photon map partitioning
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发表时间：
2008-02
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通讯作者：
M. Tamura;Hiroyuki Takizawa;Hiroaki Kobayashi
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作者：
M. Tamura;Hiroyuki Takizawa;Hiroaki Kobayashi
光子映射作为一种优秀的图像生成技术，可以模拟各种照明效果，如间接照明和焦散，只有通过全局照明模型获得，引起了人们的广泛关注。虽然光子映射可以生成高质量的图像，但它需要更昂贵的计算和更大的存储容量。本文提出了一种新的并行光子映射算法，以解决计算时间和内存需求的问题。该算法通过在并行计算机的处理单元之间分配部分光子图，可以有效地并行光子图的构建和光子搜索。当光子贴图被分割时，只有一部分光子贴图被指定给每个处理元素。因此，即使整个光子贴图相当巨大，每个处理元件也不需要大的存储空间。我们使用MPI实现了该算法，并通过在并行计算机上的实验进行了评估。实验结果表明，随着处理单元数量的增加，该算法可以显著减少光子映射的绘制时间，并节省存储空间。
Photon mapping attracts much attention as an excellent image generation technique that can simulate various lighting effects such as indirect illumination and caustics obtained only by the global illumination model. Although photon mapping can generate high-quality images, it requires more expensive calculations and a large memory capacity. In this paper, we present a new parallel photon mapping algorithm to solve the problems regarding the computing time and memory requirement. The proposed algorithm can effectively parallelize photon map construction and photon search by distributing partial photon maps among processing elements of a parallel computer. As a photon map is partitioned, only a part of the photon map is assigned to each processing element. Therefore, each processing element does not require a large memory space even if the entire photon map is quite huge. We implement the proposed algorithm using MPI and evaluate it through experiments on a parallel computer. The experimental results indicate that our algorithm can significantly reduce the rendering time of photon mapping as the number of processing elements increases, and can also save the memory space.