A parallel algorithm for construction of uniform grids

Kalojanov, Javor; Slusallek, Philipp

doi:10.1145/1572769.1572773

Cited by 60 publications

(48 citation statements)

References 21 publications

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“…Their approach was sensitive to triangles distributions spanning arbitrary number of voxels. Kalojanov and Slusallek [11] solved this problem on uniform grids and also used an appropriate grid resolution to improve the quality. Our method uses perspective grids and uniform grids, incorporating ideas to make them insensitive to triangle distribution.…”

Section: Background and Previous Workmentioning

confidence: 99%

“…On the GPU, grids have been constructed as both uniform grids [11] and perspective grids [3]. Unlike BVH or Kd-tree, grids do not possess hierarchy and therefore do not have the tree property which is extremely useful in eliminating triangles before the actual intersection checking.…”

Section: Grid Data Structurementioning

confidence: 99%

“…The cost of building a grid is low as it reduces to a sorting of triangle-voxel pairs [11]. This is one of primary reasons why rebuilding the data structure multiple times is attractive.…”

Section: Grid Data Structurementioning

confidence: 99%

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Raytracing Dynamic Scenes on the GPU Using Grids

Guntury

Narayanan

2012

IEEE Trans. Visual. Comput. Graphics

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Abstract-Raytracing dynamic scenes at interactive rates have received a lot of attention recently. We present a few strategies for high performance raytracing on a commodity GPU. The construction of grids needs sorting, which is fast on today's GPUs. The grid is thus the acceleration structure of choice for dynamic scenes as per-frame rebuilding is required. We advocate the use of appropriate data structures for each stage of raytracing, resulting in multiple structure building per frame. A perspective grid built for the camera achieves perfect coherence for primary rays. A perspective grid built with respect to each light source provides the best performance for shadow rays. Spherical grids handle lights positioned inside the model space and handle spotlights. Uniform grids are best for reflection and refraction rays with little coherence. We propose an Enforced Coherence method to bring coherence to them by rearranging the ray to voxel mapping using sorting. This gives the best performance on GPUs with only user-managed caches. We also propose a simple, Independent Voxel Walk method, which performs best by taking advantage of the L1 and L2 caches on recent GPUs. We achieve over 10 fps of total rendering on the Conference model with one light source and one reflection bounce, while rebuilding the data structure for each stage. Ideas presented here are likely to give high performance on the future GPUs as well as other manycore architectures.

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Section: Background and Previous Workmentioning

confidence: 99%

Section: Grid Data Structurementioning

confidence: 99%

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Raytracing Dynamic Scenes on the GPU Using Grids

Guntury

Narayanan

2012

IEEE Trans. Visual. Comput. Graphics

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“…Após calcular a equação da reta de interseção para cada uma das faces do elemento, calculamos o ponto mais próximo do fragmento em cada uma das retas. O ponto da reta mais próximo ao fragmentoé calculado como: (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19) onde b ié a coordenada baricêntrica de p m em relação ao vértice i do triângulo e v rié a coordenada do vértice i no espaço da superfície renderizada.…”

Section: Triângulounclassified

“…Por essa razão, optamos por usar uma grade uniforme. Nossa implementação de grade uniforme foi baseada na estrutura apresentada em (13,11,12), onde cada célula da grade possui uma lista das primitivas gráficas que se sobrepõem a célula e toda estruturaé armazenada de maneira compacta na forma de dois vetores de dados. Este trabalho implementa ainda duas variações desta estrutura, uma grade hierárquica de dois níveis e uma grade de centróides, ambas armazenadas da mesma maneira compacta.…”

Section: Introductionunclassified

Visualização De Seções De Corte Arbitrárias De Malhas Não Estruturadas

FRANCESCHIN¹

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Aos meus pais e minha família. Ao meu Orientador Waldemar, por ter me dado a oportunidade de realizar este trabalho e confiar no meu potencial.Aos meus amigos César Palomo, Chrystiano Araújo, Eduardo Ceretta, Fábio Miranda, Frederico Abraham e Rodrigo Espinha.A CAPES, PUC-Rio e Tecgraf pelos auxílios concedidos que viabilizaram este trabalho. Este trabalho propõe um método eficiente para o mapeamento de campos escalares de malhas não estruturadas em seções de corte arbitrárias. Tratase de um método de renderização direta (a interseção da superfície com o modelo nãoé extraída) que usa a GPU para garantir bom desempenho. A idéia básica do método propostoé utilizar o rasterizador da placa gráfica para gerar os fragmentos da superfície de corte e calcular a interseção de cada fragmento com o modelo em GPU. Para isso,é necessário testar a localização de cada fragmento na malha não estruturada de maneira eficiente. Como estrutura de aceleração, foram testadas três variações de grades regulares para armazenar os elementos (células) da malha, e cada elementoé representado pela lista de planos de suas faces, facilitando o teste de pertinência fragmento-elemento. Uma vez determinado o elemento que contém o fragmento, são aplicados procedimentos para interpolar o campo escalar e para identificar se o fragmento está próximoà fronteira do elemento, a fim de representar o aramado (wireframe) da malha na superfície de corte. Resultados obtidos demonstram a eficácia e a eficiência do método proposto. Palavras-chaveSeção de corte ; Malhas não estruturadas ; Programação em GPU. For the visualization of scalar fields in volume data, the use of cross sections is an effective technique to inspect the field variation inside the domain. The technique consists in mapping, on the cross section surfaces, a colormap that represents the scalar field on the surface-volume intersection. In this work, we propose an efficient method for mapping scalar fields of unstructured meshes on arbitrary cross sections. It is a direct-rendering method (the intersection of the surface and the model is not extracted) that uses GPU to ensure efficiency. The basic idea is to use the graphics rasterizer to generate the fragments of the cross-section surface and to compute the intersection of each fragment with the model. For this, it is necessary to test the location of each fragment with respect to the unstructured mesh in an efficient way. As acceleration data structure, we tested three variations of regular grids to store the elements (cells) of the mesh, and each element is represented by the list of face planes, easing the in-out test between fragments and elements. Once the element that contains the fragment is determined, it is applied procedures to interpolate the scalar field and to check if the fragment is close to the element boundary, to reveal the mesh wireframe on the surface. Achieved results demonstrate the effectiveness and the efficiency of the proposed method.

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