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Scalable data servers for large multivariate volume visualization

IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2006年第5期12卷 1291-1298页

作者： Glatter, Markus Mollenhour, Colin Huang, Jian Gao, Jinzhu Univ Tennessee Knoxville TN 37996 USA Oak Ridge Natl Lab Oak Ridge TN USA

Volumetric datasets with multiple variables on each voxel over multiple time steps are often complex, especially when considering the exponentially large attribute space formed by the variables in combination with the spatial and temporal dimensions. It is intuitive, practical, and thus often desirable, to interactively select a subset of the data from within that high-dimensional value space for efficient visualization. This approach is straightforward to implement if the dataset is small enough to be stored entirely in-core. However, to handle datasets sized at hundreds of gigabytes and beyond, this simplistic approach becomes infeasible and thus, more sophisticated solutions are needed. In this work, we developed a system that supports efficient visualization of an arbitrary subset, selected by range-queries, of a large multivariate time-varying dataset. By employing specialized data structures and schemes of data distribution, our system can leverage a large number of networked computers as parallel data servers, and guarantees a near optimal load-balance. We demonstrate our system of scalable data servers using two large time-varying simulation datasets.

关键词： parallel and distributed volume visualization large data set visualization multi-variate visualization volume visualization

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visualization and analysis of large data collections: a case study applied to confocal microscopy data

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2006年第5期12卷 1251-1258页

作者： de Leeuw, Wim Verschure, Pernette J. van Liere, Robert CWI Ctr Math & Comp Sci NL-1009 AB Amsterdam Netherlands

In this paper we propose an approach in which interactive visualization and analysis are combined with batch tools for the processing of large data collections. large and heterogeneous data collections are difficult to analyze and pose specific problems to interactive visualization. Application of the traditional interactive processing and visualization approaches as well as batch processing encounter considerable drawbacks for such large and heterogeneous data collections due to the amount and type of data. Computing resources are not sufficient for interactive exploration of the data and automated analysis has the disadvantage that the user has only limited control and feedback on the analysis process. In our approach, an analysis procedure with features and attributes of interest for the analysis is defined interactively. This procedure is used for off-line processing of large collections of data sets. The results of the batch process along with "visual summaries" are used for further analysis. visualization is not only used for the presentation of the result, but also as a tool to monitor the validity and quality of the operations performed during the batch process. Operations such as feature extraction and attribute calculation of the collected data sets are validated by visual inspection. This approach is illustrated by an extensive case study, in which a collection of confocal microscopy data sets is analyzed.

关键词： biomedical visualization features in volume data sets large data set visualization

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visualization and analysis of large data collections: a case study applied to confocal microscopy data

Visualization and analysis of large data collections: a case...

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IEEE visualization Conference (Vis 2006)/IEEE Symposium on Information visualization (InfoVis 2006)

作者： de Leeuw, Wim Verschure, Pernette J. van Liere, Robert CWI Ctr Math & Comp Sci NL-1009 AB Amsterdam Netherlands

关键词： biomedical visualization features in volume data sets large data set visualization

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A contract based system for large data visualization

A contract based system for large data visualization

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IEEE visualization 2005 Conference

作者： Childs, H Brugger, E Bonnell, K Meredith, J Miller, M Whitlock, B Max, N Univ Calif Davis Davis CA 95616 USA

ISBN: (纸本)0780394623

VisIt is a richly featured visualization tool that is used to visualize some of the largest simulations ever run. The scale of these simulations requires that optimizations are incorporated into every operation VisIt performs. But the set of applicable optimizations that VisIt can perform is dependent on the types of operations being done. Complicating the issue, VisIt has a plugin capability that allows new, unforeseen components to be added, making it even harder to determine which optimizations can be applied. We introduce the concept of a contract to the standard data flow network design. This contract enables each component of the data flow network to modify the set of optimizations used. In addition, the contract allows for new components to be accommodated gracefully within VisIt's data flow network system.

关键词： large data set visualization data flow networks contract-based system

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Scalable data servers for large multivariate volume visualization

Scalable data servers for large multivariate volume visualiz...

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IEEE visualization Conference (Vis 2006)/IEEE Symposium on Information visualization (InfoVis 2006)

作者： Glatter, Markus Mollenhour, Colin Huang, Jian Gao, Jinzhu Univ Tennessee Knoxville TN 37996 USA Oak Ridge Natl Lab Oak Ridge TN USA

关键词： parallel and distributed volume visualization large data set visualization multi-variate visualization volume visualization

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Real-time optimal adaptation for planetary geometry and texture: 4-8 tile hierarchies

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2005年第4期11卷 355-368页

作者： Hwa, LM Duchaineau, MA Joy, KI Lawrence Livermore Natl Lab Livermore CA 94551 USA Univ Calif Davis Inst Data Anal & Visualizat Davis CA 95616 USA Univ Calif Davis Dept Comp Sci Davis CA 95616 USA

The real-time display of huge geometry and imagery databases involves view-dependent approximations, typically through the use of precomputed hierarchies that are selectively refined at runtime. A classic motivating problem is terrain visualization in which planetary databases involving billions of elevation and color values are displayed on PC graphics hardware at high frame rates. This paper introduces a new diamond data structure for the basic selective-refinement processing, which is a streamlined method of representing the well-known hierarchies of right triangles that have enjoyed much success in real-time, view-dependent terrain display. Regular-grid tiles are proposed as the payload data per diamond for both geometry and texture. The use of 4-8 grid refinement and coarsening schemes allows level-of-detail transitions that are twice as gradual as traditional quadtree-based hierarchies, as well as very high-quality low-pass filtering compared to subsampling-based hierarchies. An out-of-core storage organization is introduced based on Sierpinski indices per diamond, along with a tile preprocessing framework based on fine-to-coarse, same-level, and coarse-to-fine gathering operations. To attain optimal frame-to-frame coherence and processing-order priorities, dual split and merge queues are developed similar to the Realtime Optimally Adapting Meshes ( ROAM) Algorithm, as well as an adaptation of the ROAM frustum culling technique. Example applications of lake-detection and procedural terrain generation demonstrate the flexibility of the tile processing framework.

关键词： large data set visualization level-of-detail techniques view dependent visualization adaptive textures out-of-core algorithms procedural terrain generation

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Hardware-independent Clipmapping

Hardware-independent Clipmapping

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15th International Conference in Central Europe on Computer Graphics, visualization and Computer Vision

作者： Seoane, Antonio Taibo, Javier Hernandez, Luis Lopez, Ruben Jaspe, Alberto Univ A Coruna Sch Civil Engn La Coruna 15071 Spain

ISBN: (纸本)9788086943985

We present a technique for efficient management of large textures and its real-time application to geometric models. The proposed technique is inspired by the clipmap [12] idea, that caches in video memory a subset of the texture mipmap pyramid. Based on this concept, we define some structures and a different management allowing its implementation on a personal computer without specific graphics hardware. Finally, we present the results of the application in a terrain visualization system, using several simultaneous textures with a detail up to 0.25 meters per texel, covering a 60,000 km(2) area.

关键词： Terrain visualization multiresolution visualization large data set visualization level-of-detail techniques texture mapping clipmap mipmap texture caching

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Real-time optimal adaptation for planetary geometry and texture: 4-8 tile hierarchies

Real-time optimal adaptation for planetary geometry and text...

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IEEE visualization 2004 Conference

关键词： large data set visualization level-of-detail techniques view dependent visualization adaptive textures out-of-core algorithms procedural terrain generation

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Fast implicit KD-trees: Accelerated isosurface ray tracing and maximum intensity projection for large scalar fields

Fast implicit KD-trees: Accelerated isosurface ray tracing a...

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9th International Conference on Computer Graphics and Imaging

作者： GroB, Matthias Lojewski, Carsten Bertram, Martin Hagen, Hans CC High Performance Computing Fraunhofer ITWM Germany Department of Computer Sciences University of Kaiserslautern Germany

ISBN: (纸本)9780889866447

Many scientific data sets are 3D or 4D scalar fields, for which typically isosurface- and volume visualization methods are used to extract infon-nation. These data sets are either massively complex (e.g., seismic data sets), or steadily increasing in size due to the permanently improving resolutions of different 3D scanners (e.g., CT- and MRTscanners) or calculation results (e.g., CFD-simulations). Only algorithms that scale well to data set complexity are suited to visualize those increasing data sets. Isosurface ray tracing and maximum intensity projection (MIP) accelerated through implicit KD-trees have a logarithmic dependency between visualization time and scene size, making them ideal algorithms for the visualization of massively complex scalar fields. Furthermore is ray tracing efficiently parallelized on the more and more commonly used shared memory machines (e.g., desktop machines with several multicore processors) and may be used to realize advanced shading effects like shadows and reflections. We introduce new optimized implicit KD-trees which allow on today's desktop computers interactive isosurfacing and MIP of data sets that are bigger than one half of the machine's main memory.

关键词： iso-surface extraction maximum intensity projection time-varying volume data large data set visualization implicit KD-trees ray tracing

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Efficient point-based isosurface exploration using the span-triangle 04

Efficient point-based isosurface exploration using the span-...

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IEEE visualization 2004 Conference

作者： von Rymon-Lipinski, B Hanssen, N Jansen, T Ritter, L Keeve, E Surgical Systems Laboratory

ISBN: (纸本)0780387880

We introduce a novel span-triangle data structure, based on the span-space representation for isosurfaces. It stores all necessary cell information for dynamic manipulation of the isovalue in an efficient way. We have found that using our data structure in combination with point-based techniques, implemented on graphics hardware, effects in real-time rendering and exploration. Our extraction algorithm utilizes an incremental and progressive update scheme, enabling smooth interaction without significant latency. Moreover, the corresponding visualization pipeline is capable of processing large data sets by utilizing, all three levels of memory: disk, system and graphics. We address practical usability in actual medical applications. achieving a new level of interactivity.

关键词： point-based visualization isosurfaces hardware acceleration large data set visualization visualization in medicine

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