Visibility culling has the potential to accelerate largedatavisualization in significant ways. Unfortunately, existing algorithms do not scale well when parallelized, and require full re-computation whenever the opa...
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Visibility culling has the potential to accelerate largedatavisualization in significant ways. Unfortunately, existing algorithms do not scale well when parallelized, and require full re-computation whenever the opacity transfer function is modified. To address these issues, we have designed a Plenoptic Opacity Function (POF) scheme to encode the view-dependent opacity of a volume block. POFs are computed off-line during a pre-processing stage, only once for each block. We show that using POFs is (i) an efficient, conservative and effective way to encode the opacity variations of a volume block for a range of views, (ii) flexible for re-use by a family of opacity transfer functions without the need for additional off-line processing, and (iii) highly scalable for use in massively parallel implementations. Our results confirm the efficacy of POFs for visibility culling in large-scale parallel volume rendering;we can interactively render the Visible Woman dataset using software ray-casting on 32 processors, with interactive modification of the opacity transfer function on-the-fly.
The proceedings contain 16 papers. The topics discussed include: rapid emission tomography reconstruction;chronovolumes: a direct rendering technique for visualizing time-varying data;spatial transfer functions: a uni...
ISBN:
(纸本)1581137451
The proceedings contain 16 papers. The topics discussed include: rapid emission tomography reconstruction;chronovolumes: a direct rendering technique for visualizing time-varying data;spatial transfer functions: a unified approach to specifying deformation in volume modeling and animation;real-time volume manipulation;volumetric ablation rendering;the design and evaluation of a pipelined image compositing device for massively parallel volume rendering;OpenVL: the open volume library;accuracy-based sampling and reconstruction with adaptive grid for parallel hierarchical tetrahedrization;multiresolution volume simplification and polygonization;out-of-core encoding of large tetrahedral meshes;cell projection of convex polyhedra;hybrid forward resampling and volume rendering;and an interactive volume visualization system for transient flow analysis.
A number of problems are well suited for volumetric representation for both simulation and storage, however, the large amount of data that needs to be processed and rendered with these volumes makes interactive manipu...
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A number of problems are well suited for volumetric representation for both simulation and storage, however, the large amount of data that needs to be processed and rendered with these volumes makes interactive manipulation extremely challenging. We present a scalable PC cluster system (VG cluster) designed specifically to enable simultaneous volumetric computation and visualization, using compositing hardware devices and the latest PC graphics accelerators. We demonstrate the flexibility and performance of this system with several different applications that include reaction-diffusion simulation, volumetric image processing, and vector field visualization. We also discuss how to improve the visual computing performance of this system with some load balancing techniques.
We describe a new set of parallel rendering components for VTK, the visualization toolkit. The parallel rendering units allow for the rendering of vast quantities of geometry with a focus on cluster computers. Further...
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We describe a new set of parallel rendering components for VTK, the visualization toolkit. The parallel rendering units allow for the rendering of vast quantities of geometry with a focus on cluster computers. Furthermore, the geometry may be displayed on tiled displays at full or reduced resolution. We demonstrate an interactive VTK application processing an isosurface consisting of nearly half a billion triangles and displaying on a power wall with a total resolution of 63 million pixels. We also demonstrate an interactive VTK application displaying the same geometry on a desktop connected to the cluster via a TCP/IP socket over 100BASE-T Ethernet.
The recent advance of graphics hardware allowed real-time volume rendering of structured grids using a 3D texturing approach. The next challenging problem is to extend the algorithms to time-varying volumetric data (4...
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The recent advance of graphics hardware allowed real-time volume rendering of structured grids using a 3D texturing approach. The next challenging problem is to extend the algorithms to time-varying volumetric data (4D functions), which consume more storage and are not directly supported in current graphics hardware. Here we present a new visualization technique that includes (1) a compression scheme of sparse 4D functions into 3D textures, and (2) a visualization algorithm that decompress the stored data from the 3D textures using the programmability of fragment shaders, allowing real-time visualization of such data. We illustrate the system in action with datasets resulting from computational fluid dynamics simulations.
We present a new visibility-based prefetching algorithm for interactive out-of-core rendering of large models on an inexpensive PC. Using an approximate visibility technique, we can very accurately and efficiently det...
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ISBN:
(纸本)9780769520919
We present a new visibility-based prefetching algorithm for interactive out-of-core rendering of large models on an inexpensive PC. Using an approximate visibility technique, we can very accurately and efficiently determine which geometry will be visible in the near future and prefetch that geometry from disk before it must be rendered. Our prefetching algorithm is a key part of a visualization system capable of rendering a 13-million triangle model with 99% accuracy at interactive frame rates. Our prefetching algorithm is the first of its kind to be based on a from-point visibility technique, and enables interactive rendering on a commodity PC, as opposed to expensive high-end graphics workstations or parallel machines.
A new approach for largedataset isosurface extraction is presented. The approach's aim is efficient parallel isosurfacing when the dataset cannot be processed entirely in-core. The approach focuses on reducing th...
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A new approach for largedataset isosurface extraction is presented. The approach's aim is efficient parallel isosurfacing when the dataset cannot be processed entirely in-core. The approach focuses on reducing the memory requirement and optimizing disk I/O while achieving a balanced load. In particular, an accurate model of isosurface extraction time is exploited to evenly distribute work across processors. The approach achieves processing efficiency by also avoiding unnecessary processing for portions of the dataset that are not intersected by the isosurface. To reduce the redundant computations and the storage requirements, a flexible, variably-granular data structure is utilized, thereby achieving excellent time and space performance.
While commodity computing and graphics hardware has increased in capacity and dropped in cost, it is still quite difficult to make effective use of such systems for general-purpose parallelvisualization and graphics....
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While commodity computing and graphics hardware has increased in capacity and dropped in cost, it is still quite difficult to make effective use of such systems for general-purpose parallelvisualization and graphics. We describe the results of a recent project that provides a software infrastructure suitable for general-purpose use by parallelvisualization and graphics applications. Our work combines and extends two technologies: chromium, a stream-oriented framework that implements the OpenGL programming interface; and OpenRM scene graph, a pipelined-parallel scene graph interface for graphicsdata management. Using this combination, we implement a sort-first, distributed memory, parallel volume rendering application. We describe the performance characteristics in terms of bandwidth requirements and highlight key algorithmic considerations needed to implement the sort-first system. We characterize system performance using a distributed memory parallel volume rendering application, and present performance gains realized by using scene specific knowledge to accelerate rendering by reducing network traffic. The contribution of this work is an exploration of general-purpose, sort-first architecture performance characteristics as applied to distributed memory, commodity hardware, along with a description of the algorithmic support needed to realize parallel, sort-first implementations.
We describe a feature extraction and tracking algorithm for AMR (adaptive mesh refinement) datasets that operates within a distributed computing environment. Because features can span multiple refinement levels and mu...
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We describe a feature extraction and tracking algorithm for AMR (adaptive mesh refinement) datasets that operates within a distributed computing environment. Because features can span multiple refinement levels and multiple processors, tracking must be performed across time, across levels, and across processors. The resulting visualization is represented as a "feature tree". A feature contains multiple parts corresponding to different levels of refinements. The feature tree allows a viewer to determine that a feature splits or merges at the next refinement level, and allows a viewer to extract and isolate a multilevel isosurface and watch how that surface changes over both time and space. The algorithm is implemented within a computational steering environment, which enables the visualization routines to operate on the data in-situ (while the simulation is ongoing).
Recent advances in volume scanning techniques have made the task of acquiring volume data of 3-D objects easier and more accurate. Since the quantity of such acquired data is generally very large, a volume model capab...
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ISBN:
(纸本)1581137451
Recent advances in volume scanning techniques have made the task of acquiring volume data of 3-D objects easier and more accurate. Since the quantity of such acquired data is generally very large, a volume model capable of compressing data while maintaining a specified accuracy is required. The objective of this work is to construct a multi resolution tetrahedra representation of input volume data. This representation adapts to local field properties while preserving their discontinuities. In this paper, we present an accuracy-based adaptive sampling and reconstruction technique, we call an adaptive grid, for hierarchical tetrahedrization of C1 continuous volume data. We have developed a parallel algorithm of adaptive grid generation that recursively bisects tetrahedra gird elements by increasing the number of grid nodes, according to local field properties and such as orientation and curvature of isosurfaces, until the entire volume has been approximated within a specified level of view-invariant accuracy. We have also developed a parallel algorithm that detects and presents both C0 and C1 discontinuities of field values, without the formation of cracks which normally occur during independent subdivision. Experimental results demonstrate the validity and effusiveness of the proposed approach.
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