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Surface area heuristic construction KD (K-dimension) tree parallel method on graphics processing unit

A surface area heuristic, graphics processor technology, applied in the direction of processor architecture/configuration, image data processing, 3D image processing, etc., to achieve the effect of improving quality

Inactive Publication Date: 2012-04-25
ZHEJIANG UNIV
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Problems solved by technology

[0005] The present invention proposes a parallel method for efficiently constructing a SAH KD-Tree for a 3D model on a GPU stream architecture, to solve the problem of efficiently constructing a high-quality KD-Tree in a ray tracing rendering application on the current GPU stream computing architecture The problem

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  • Surface area heuristic construction KD (K-dimension) tree parallel method on graphics processing unit
  • Surface area heuristic construction KD (K-dimension) tree parallel method on graphics processing unit
  • Surface area heuristic construction KD (K-dimension) tree parallel method on graphics processing unit

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Embodiment Construction

[0024] Below in conjunction with accompanying drawing, the present invention will be further described, as figure 1 Shown, the present invention comprises the following steps:

[0025] Step 1: Input 3D model data, and perform triangular meshing for 3D scenes without triangular meshes. The scene data is then stored in the GPU's video memory. The data contained in the 3D scene is two arrays, that is, the fixed-point array of the triangular patch and the vertex index array of the triangular patch.

[0026] Step 2: According to the number n of triangle faces of the input 3D model data, allocate a node list nodelist with a size of n, and split the queues iqueue and oqueue with a size of n nodes. If overflow occurs during the construction process, the size of nodelist, iqueue and oqueue will be doubled. The data structure of nodelist is 5 arrays: tlist (triangle patch index), pf_lch (the address of the first triangle patch of the node or the left node pointer), pn_rch (the number...

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Abstract

The invention discloses a surface area heuristic construction KD (K-dimension) tree parallel method on a graphics processing unit. A traditional serial method on a CPU (central processing unit) can not well play the powerful parallel computing capability of a GPU (graphics processing unit) streaming architecture. The surface area heuristic construction KD tree parallel method disclosed by the invention comprises the following steps of: inputting data description of a 3D (three-dimensional) scene; designing a data structure of a KD-Tree space partition structure; performing SAH (surface area heuristic) optimization function parallel computing; and performing parallel triangle mesh cutting and sequencing. According to the method disclosed by the invention, the high-quality KD-Tree space partition structure can be constructed for an input 3D model on the GPU streaming architecture in a high-efficient and parallel manner, and the efficiency of the method disclosed by the invention is higher than that of the traditional serial and parallel methods on the CPU; furthermore, in the aspect of acceleration ratio of interaction with rays, the method disclosed by the invention is much higher than a BVH (bounding volume hierarchy)-Tree acceleration method which is currently relatively popular on the GPU.

Description

technical field [0001] The invention relates to the field of parallel computing of graphics processors, in particular to a parallel construction method of a 3D model space subdivision structure. Background technique [0002] In computer graphics, in order to generate realistic photo-level effects, it is necessary to simulate the lighting principles of real scenes. That is, by tracing each ray and accurately calculating its reflection, refraction and shadow, a photo-realistic rendering effect can be obtained. In the entire calculation process, the most time-consuming process is the intersecting process of light and 3D scene. The existing various versions of ray tracing methods and their variants all need to space-segment the scene first and build a space-segmenting tree; then perform ray tracing. In the method of space subdivision of the scene, there are mainly three space subdivision methods, Octree, BVH-tree and KD-tree. Although these three spatial subdivision structure...

Claims

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Application Information

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IPC IPC(8): G06T15/06G06T1/20
Inventor 吴哲锋赵福凯刘新国
Owner ZHEJIANG UNIV
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