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Parallel optimization of the ray-tracing algorithm based on the HPM model

机译:基于HPM模型的光线跟踪算法的并行优化

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摘要

This paper proposes a parallel computing analysis model HPM and analyzes the parallel architecture of CPU-GPU based on this model. On this basis, we study the parallel optimization of the ray-tracing algorithm on the CPU-GPU parallel architecture and give full play to the parallelism between nodes, the parallelism of the multi-core CPU inside the node, and the parallelism of the GPU, which improve the calculation speed of the ray-tracing algorithm. This paper uses the space division technology to divide the ground data, constructs the KD-tree organization structure, and improves the construction method of KD-tree to reduce the time complexity of the algorithm. The ground data is evenly distributed to each computing node, and the computing nodes use a combination of CPU-GPU for parallel optimization. This method dramatically improves the drawing speed while ensuring the image quality and provides an effective means for quickly generating photorealistic images.
机译:本文提出了一个并行计算分析模型HPM,并根据该模型分析CPU-GPU的并行架构。 在此基础上,我们研究了CPU-GPU并行架构上的光线跟踪算法的并行优化,并充分发挥节点之间的并行性,节点内的多核CPU的并行性,以及GPU的并行性 ,提高了光线跟踪算法的计算速度。 本文采用空间划分技术划分地面数据,构建KD树组织结构,提高KD树的施工方法,降低算法的时间复杂性。 地面数据均匀地分布到每个计算节点,并且计算节点使用CPU-GPU的组合进行并行优化。 该方法在确保图像质量的同时显着提高拉伸速度,并提供了快速生成光电型图像的有效手段。

著录项

  • 来源
    《Journal of supercomputing》 |2021年第9期|10307-10332|共26页
  • 作者单位

    Beijing Inst Technol Sch Comp Sci & Technol Beijing 100081 Peoples R China;

    Beijing Inst Technol Sch Comp Sci & Technol Beijing 100081 Peoples R China;

    Beijing Inst Sci & Technol Informat Beijing 100044 Peoples R China;

    Beijing Inst Technol Sch Comp Sci & Technol Beijing 100081 Peoples R China;

    Minjiang Univ Fujian Prov Key Lab Informat Proc & Intelligent C Fuzhou 350117 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Ray tracing; KD-tree; HPM model; CPU#8211; GPU parallel acceleration;

    机译:射线追踪;kd树;嗯模型;CPU–GPU并行加速度;

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