Abstract:In this paper we propose several significant improvements to the hardware ray casting algorithm for unstructured meshes proposed byWeiler et al [14]. In their work, ray casting computation is entirely performed in the GPU by advancing intersections against the mesh while evaluating the volume rendering integral. Our contributions can be divided into three categories. First, we propose an alternate representation for mesh data in 2D textures that is more compact and efficient, compared to the 3D textures used in the original work. Second, we use a tile-based subdivision of the screen that allows computation to proceed only at places where it is required, thus reducing fragment processing in the GPU. Finally, we do not introduce imaginary cells that fill space caused by non-convexities of the mesh. Instead, we use a depth-peeling approach that captures when rays re-enter the mesh, which is much more general and does not require a convexification algorithm.We report results on an ATI 9700 Pro, the same hardware used by Weiler et al in their work. Due to the use of the 2D textures and the tiling, our technique is actually much faster than their work, while at the same time being more general, since it can render true non-convex meshes, as compared to their work, which is limited to convex (or convexified ) ones. On the Blunt Fin, our code renders between 400 Ktet/sec to 1.3 Mtet/sec. GPU-based Tiled AbstractIn this paper we propose several significant improvements to the hardware ray casting algorithm for unstructured meshes proposed by Weiler et al [14]. In their work, ray casting computation is entirely performed in the GPU by advancing intersections against the mesh while evaluating the volume rendering integral. Our contributions can be divided into three categories. First, we propose an alternate representation for mesh data in 2D textures that is more compact and efficient, compared to the 3D textures used in the original work. Second, we use a tile-based subdivision of the screen that allows computation to proceed only at places where it is required, thus reducing fragment processing in the GPU. Finally, we do not introduce imaginary cells that fill space caused by non-convexities of the mesh. Instead, we use a depth-peeling approach that captures when rays re-enter the mesh, which is much more general and does not require a convexification algorithm.We report results on an ATI 9700 Pro, the same hardware used by Weiler et al in their work. Due to the use of the 2D textures and the tiling, our technique is actually much faster than their work, while at the same time being more general, since it can render true non-convex meshes, as compared to their work, which is limited to convex (or convexified) ones. On the Blunt Fin, our code renders between 400 Ktet/sec to 1.3 Mtet/sec.

The parallel vectors (PV) operator is a feature extraction approach for defining line-type features such as creases (ridges and valleys) in scalar fields, as well as separation, attachment, and vortex core lines in vector fields. In this work, we extend PV feature extraction to higher-order data represented by piecewise analytical functions defined over grid cells. The extraction uses PV in two distinct stages. First, seed points on the feature lines are placed by evaluating the inclusion form of the PV criterion with reduced affine arithmetic. Second, a feature flow field is derived from the higher-order PV expression where the features can be extracted as streamlines starting at the seeds. Our approach allows for guaranteed bounds regarding accuracy with respect to existence, position, and topology of the features obtained. The method is suitable for parallel implementation and we present results obtained with our GPU-based prototype. We apply our method to higher-order data obtained from discontinuous Galerkin fluid simulations.

Traditional shadow maps store a single depth value per cell, leading to a binary outcome by the shadow test (either lit or in shadow), and are prone to produce aliased shadow borders. We present a new approach that produces better estimates of shadow percentages and, in combination with percentage closer filtering (PCF), reduces aliasing artifacts using smaller kernel sizes. The new algorithm extends the notions of shadow maps and shadow tests to support the representation of multiple depth values per shadow map cell, as well as multi-valued shadow tests. This new approach has the potential for hardware implementation, but can also be implemented exploiting the programmable capabilities of recent graphics cards.

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