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史可鉴, 王斌, 朱恬倩, 张慧, 侯兆国. GPU上的kD-tree雷达模拟加速[J]. 计算机辅助设计与图形学学报, 2010, 22(3): 440-448.
引用本文: 史可鉴, 王斌, 朱恬倩, 张慧, 侯兆国. GPU上的kD-tree雷达模拟加速[J]. 计算机辅助设计与图形学学报, 2010, 22(3): 440-448.
Shi Kejian, Wang Bin, Zhu Tianqian, Zhang Hui, Hou Zhaoguo. Radar Simulation with kD-Tree on the GPU[J]. Journal of Computer-Aided Design & Computer Graphics, 2010, 22(3): 440-448.
Citation: Shi Kejian, Wang Bin, Zhu Tianqian, Zhang Hui, Hou Zhaoguo. Radar Simulation with kD-Tree on the GPU[J]. Journal of Computer-Aided Design & Computer Graphics, 2010, 22(3): 440-448.

GPU上的kD-tree雷达模拟加速

Radar Simulation with kD-Tree on the GPU

  • 摘要: 为了加速对雷达系统的计算机仿真模拟,提出一种基于kD-tree的GPU并行加速算法.采用CUDA实现了多种kD-tree的并行遍历算法,并对这些遍历算法性能进行比较分析,从中筛选出了最适合在GPU上进行雷达模拟加速的Shortstack-kD算法.实验结果表明,Shortstack-kD算法不仅对不同种类的场景都能带来明显的效率提升,还可以根据场景的不同情况控制Shortstack-kD的栈长度,以达到算法的最高性能和最大灵活性;在CPU上进行建树的过程中还针对雷达模拟的应用需求进行了优化.

     

    Abstract: This paper presents a GPU-based parallel algorithm for radar simulation acceleration.The approach uses kD-tree as its acceleration structure.We implement several traversal algorithms of kD-tree on CUDA,and then find through a comparison test that the Shortstack-kD is the most suitable structure.Experimental results show that Shortstack-kD is always efficient for different models,with stack length can adjustable to control the balance between performance and flexibility.In addition,an optimization technique based on CUDA is applied to data structure of the scene and rays,suitable for device memory accessing of GPU.

     

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