2011
DOI: 10.1177/1094342011403785
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Fast GPU perspective grid construction and triangle tracing for exhaustive ray tracing of highly coherent rays

Abstract: In this article, we address the problem of computing, storing and sorting, at an interactive rate, all of the intersections between millions of triangles (a 3D scene) and millions of rays starting from the same point. In this paper we focus on the fast GPU construction of a grid in projective space referencing the triangles of a 3D scene. We introduce a fast GPU algorithm used to build a grid of the rays constituting the scene, in the same projective space. This ray-based grid is computed during the initializa… Show more

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Cited by 3 publications
(2 citation statements)
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“…In addition to multicore processors, the rapid development of graphic processing units (GPUs) provides a new opportunity to solve the computation bottleneck of simulating stochastic computing elements (SCEs). Due to the low cost and parallel computing capability of the GPUs, GPU computing has recently been used for a wide range of high-performance computing applications (Vigueras et al, 2010;Perrotte and Saupin, 2010;Monitzer, 2010;Lastras-Montano et al, 2010). Benefiting from the GPU hardware, applications can often achieve more than 100 times performance speedup for digital signal processing, physical simulations, biomedical imaging, geologic computation (Myre et al, to appear;Walsh et al, 2009;Bailey et al, 2009), and other fields.…”
Section: Introductionmentioning
confidence: 98%
“…In addition to multicore processors, the rapid development of graphic processing units (GPUs) provides a new opportunity to solve the computation bottleneck of simulating stochastic computing elements (SCEs). Due to the low cost and parallel computing capability of the GPUs, GPU computing has recently been used for a wide range of high-performance computing applications (Vigueras et al, 2010;Perrotte and Saupin, 2010;Monitzer, 2010;Lastras-Montano et al, 2010). Benefiting from the GPU hardware, applications can often achieve more than 100 times performance speedup for digital signal processing, physical simulations, biomedical imaging, geologic computation (Myre et al, to appear;Walsh et al, 2009;Bailey et al, 2009), and other fields.…”
Section: Introductionmentioning
confidence: 98%
“…Zhou [15] greatly improved ray tracing by implementing Kdtree building on GPU. And also Perrotte [16] and Guntury [17] implemented Grids building under the perspective view and ray tracing with Grids on GPU.…”
Section: Introductionmentioning
confidence: 99%