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8th IEEE symposium on Large-Scale Data Analysis and visualization (LDAV)

作者： Moreland, Kenneth Sandia Natl Labs Livermore CA 94550 USA

ISBN: (纸本)9781538668733

A key component of most large-scale rendering systems is a parallel image compositing algorithm, and the most commonly used compositing algorithms are binary swap and its variants. Although shown to be very efficient, one of the classic limitations of binary swap is that it only works on a number of processes that is a perfect power of 2. Multiple variations of binary swap have been independently introduced to overcome this limitation and handle process counts that have factors that are not 2. To date, few of these approaches have been directly compared against each other, making it unclear which approach is best. This paper presents a fresh implementation of each of these methods using a common software framework to make them directly comparable. These methods to run binary swap with odd factors are directly compared. The results show that some simple compositing approaches work as well or better than more complex algorithms that are more difficult to implement.

关键词： Computing methodologies Computer graphics Rendering Computing methodologies parallel computing methodologies parallel algorithms Massively parallel algorithms

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Distributed interactive ray tracing for large volume visualization 03

Distributed interactive ray tracing for large volume visuali...

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IEEE symposium on parallel and Large-Data visualization and graphics

作者： DeMarle, DE Parker, S Hartner, M Gribble, C Hansen, C Univ Utah Salt Lake City UT 84112 USA

ISBN: (纸本)078038122X

We have constructed a distributed parallel ray tracing system that interactively produces isosurface renderings from large data sets on a cluster of commodity PCs. The program was derived from the SCI Institute's interactive ray tracer (*-Ray), which utilizes small to large shared memory platforms, such as the SGI Origin series, to interact with very large-scale data sets. Making this approach work efficiently on a cluster requires attention to numerous system-level issues, especially when rendering data sets larger than the address space of each cluster node. The rendering engine is an image parallel ray tracer with a supervisor/workers organization. Each node in the cluster runs a multi-threaded application. A minimal abstraction layer on top of TCP links the nodes, and enables asynchronous message handling. For large volumes, render threads obtain data bricks on demand from an object-based software distributed shared memory. Caching improves performance by reducing the amount of data transfers for a reasonable working set size. For large data sets, the cluster-based interactive ray tracer performs comparably with an SGI Origin system. We examine the parameter space of the renderer and provide experimental results for interactive rendering of large (7.5 GB) data sets.

关键词： visualization interactive ray tracing large data cluster computing distributed shared memory

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A unified infrastructure for parallel out-of-core isosurface extraction and volume rendering of unstructured grids

A unified infrastructure for parallel out-of-core isosurface...

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IEEE symposium on parallel and Large-Data visualization and graphics

作者： Chiang, YJ Farias, R Silva, CT Wei, B Polytech Univ Dept Comp & Informat Sci Brooklyn NY 11201 USA

ISBN: (纸本)0780372239

In this paper, we present a unified infrastructure for parallel out-of-ore isosurface extraction and volume rendering of large unstructured grids on distributed-memory parallel machines. We parallelize the out-of-core isosurface extraction algorithm of [9] and the out-of-core ZSweep technique [17] for direct volume rendering, using the meta-cell technique as a unified underlying building block. Our one-time preprocessing first partitions the dataset into meta-ells that are stored in disk. From the meta-cells, we build a BBIO tree in disk, which can be used to speed up isosurface extraction, and a bounding-box file in disk, which is used for direct volume rendering. At run-time, we use a simple self-scheduling scheme [39] to achieve load balancing among the processors, We perform several experiments on a sixteen-node cluster of PCs connected by a gigabit ethernet, using datasets as large as 6.6 million cells. For the larger datasets, we have found that both our isosurface extraction and direct volume rendering approaches are perfectly scalable up to sixteen nodes.

关键词： isosurface extraction volume rendering parallel computation out-of-core techniques scientific visualization

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visualization challenges for a new cyberpharmaceutical computing paradigm

Visualization challenges for a new cyberpharmaceutical compu...

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IEEE symposium on parallel and Large-Data visualization and graphics

作者： Turner, RJ Chaturvedi, K Edwards, NJ Fasulo, D Halpern, AL Huson, DH Kohlbacher, O Miller, JR Reinert, K Remington, KA Schwartz, R Walenz, B Yooseph, S Istrail, S Celera Genom Corp Rockville MD 20850 USA

ISBN: (纸本)0780372239

In recent years, an explosion in data has been profoundly changing the field of biology and creating the need for new areas of expertise, particularly in the handling of data. One vital area that has so far received insufficient attention is how to communicate the large quantities of diverse and complex information that is being generated. Celera has encountered a number of visualization problems in the course of developing tools for bioinformatics research, applying them to our data generation efforts, and making that data available to our customers. This paper presents several examples from Celera's experience. In the area of genomics, challenging visualization problems have come up in assembling genomes, studying variations between individuals, and comparing different genomes to one another. The emerging area of proteomics has created new visualization challenges in interpreting protein expression data, studying protein regulatory networks, and examining protein structure. These examples illustrate how the field of bioinformatics is posing new challenges concerning the communication of data that are often very different from those that have heretofore dominated scientific computing. Addressing the level of detail, the degree of complexity, and the interdisciplinary barriers that characterize bioinformatic problems can be expected to be a sizable but rewarding task for the field of scientific visualization.

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A parallel and Memory Efficient Algorithm for Constructing the Contour Tree 8

A Parallel and Memory Efficient Algorithm for Constructing t...

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IEEE Pacific visualization symposium (PacificVis)

作者： Acharya, Aditya Natarajan, Vijay Indian Inst Sci Supercomp Educ & Res Ctr Bangalore Karnataka India Indian Inst Sci Supercomp Educ & Res Ctr Dept Comp Sci & Automat Bangalore Karnataka India

ISBN: (纸本)9781467368797

The contour tree is a topological structure associated with a scalar function that tracks the connectivity of the evolving level sets of the function. It supports intuitive and interactive visual exploration and analysis of the scalar function. This paper describes a fast, parallel, and memory efficient algorithm for constructing the contour tree of a scalar function on shared memory systems. Comparisons with existing implementations show significant improvement in both the running time and the memory expended. The proposed algorithm is particularly suited for large datasets that do not fit in memory. For example, the contour tree for a scalar function defined on a 8.6 billion vertex domain (2048 x 2048 x 2048 volume data) can be efficiently constructed using less than 10GB of memory.

关键词： I.3.5 [Computer graphics]: Computational Geometry and Object Modeling SCALAR FUNCTIONS efficient algorithm Memory Memory contour Trees topological structure

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The InfoVis Toolkit

The InfoVis Toolkit

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10th Annual IEEE symposium on Information visualization (InfoVis 2004)

作者： Fekete, JD Univ Paris 11 INRIA Futurs LRI F-91405 Orsay France

ISBN: (纸本)0780387791

This article presents the InfoVis Toolkit, designed to support the creation, extension and integration of advanced 2D Information visualization components into interactive Java Swing applications. The InfoVis Toolkit provides specific data structures to achieve a fast action/feedback loop required by dynamic queries. It comes with a large set of components such as range sliders and tailored control panels required to control and configure the visualizations. These components are integrated into a coherent framework that simplifies the management of rich data structures and the design and extension of visualizations. Supported data structures currently include tables, trees and graphs. Supported visualizations include scatter plots, time series, parallel coordinates, treemaps, icicle trees, node-link diagrams for trees and graphs and adjacency matrices for graphs. All visualizations can use fisheye lenses and dynamic labeling. The InfoVis Toolkit supports hardware acceleration when available through Agile2D, an implementation of the Java graphics API based on OpenGL, achieving speedups of 10 to 200 times. The article also shows how new visualizations can be added and extended to become components, enriching visualizations as well as general applications.

关键词： information visualization toolkit graphics integration

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A flexible Java GPU-enhanced visualization framework and its applications

A flexible Java GPU-enhanced visualization framework and its...

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25th International symposium on Computer-Based Medical Systems (CBMS)

作者： Cheng, Ruida Senseney, Justin Pandya, Nishith McCreedy, Evan McAuliffe, Matthew J. Bokinsky, Alexandra Natl Inst Hlth Imaging Sci Lab Ctr Informat Technol Bethesda MD 20892 USA Geometr Tools Inc Chapel Hill NC USA

ISBN: (纸本)9781467320511

A flexible biomedical visualization framework implemented with Java, OpenGL, and OpenCL performs efficient volume rendering with large, multi-modal datasets. The,framework takes advantage of the parallel processing power on modern graphics hardware with novel Open CL and GLSL shading language implementations. The Java and GPU environment provide portable advanced biomedical image visualization applications. Several applications built on top of the GPU framework are also presented to show the extensibility of the application. These include multi-surface rendering, stereoscopic rendering, image fusion, and diffusion tensor visualization.

关键词： graphics processing unit

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Dynamic view-dependent partitioning of structured grids with complex boundaries for object-order rendering techniques

Dynamic view-dependent partitioning of structured grids with...

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1999 IEEE symposium on parallel visualization and graphics, PVGS 1999

作者： Burton, Lance C. Machiraju, Raghu Reese, Donna S. NSF Engineering Research Center for Computational Field Simulation Dept. of Computer Science Mississippi State University P.O. Box 9627 Mississippi StateMS39762 United States

ISBN: (纸本)1581132379

Object-order rendering techniques present an attractive approach to run-time visualization of structured grid data, particularly when combined with a parallel rendering paradigm such as image composition. The ability of this combination to exploit hardware exceeds that of parallel image order methods. However, certain configurations of grid boundaries prevent composition from being performed correctly. In particular, when the boundary between two partitions contains concave sections, the partitions may no longer be depth sorted correctly, a requirement for some visualization techniques such as direct volume rendering. This occurs because the concave boundary prevents even the simple ordering of two adjacent partitions. If the data may be repartitioned such that it can be depth sorted correctly, then an image composition approach is a viable option. To facilitate such an operation, we present an algorithm to analyze the geometric structure of a grid boundary and extract knowledge about how the boundary impacts depth sorting and therefore image composition. We then show through examples how this knowledge may be applied to create a set of partitions that may be properly depth sorted.

关键词： visualization

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Scalable interactive volume rendering using off-the-shelf components

Scalable interactive volume rendering using off-the-shelf co...

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IEEE symposium on parallel and Large-Data visualization and graphics

作者： Lombeyda, S Moll, L Shand, M Breen, D Heirich, A CALTECH Pasadena CA 91125 USA

ISBN: (纸本)0780372239

This paper describes an application of a second generation implementation of the Sepia architecture (Sepia-2) to interactive volumetric visualization of large rectilinear scalar fields. By employing pipelined associative blending operators in a sort-last configuration a demonstration system with 8 rendering computers sustains 24 to 28 frames per second while interactively rendering large data volumes (1024x256x256 voxels, and 512x512x512 voxels). We believe interactive performance at these frame rates and data sizes is unprecedented. We also believe these results can be extended to other types of structured and unstructured grids and a variety of GL rendering techniques including surface rendering and shadow mapping. We show how to extend our single-stage crossbar demonstration system to multi-stage networks in order to support much larger data sizes and higher image resolutions. This requires solving a dynamic mapping problem for a class of blending operators that includes Porter-Duff compositing operators.

关键词： sort-last parallel cluster shear-warp volume rendering ray-casting shadow mapping CFD VolumePro OpenGL VIA Clos

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Scalable data servers for large multivariate volume visualization

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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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