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parallel Computation of 2D Morse-Smale Complexes

ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2012年第10期18卷 1757-1770页

作者： Shivashankar, Nithin Senthilnathan, M. Natarajan, Vijay Indian Inst Sci Dept Comp Sci & Automat Bangalore 560012 Karnataka India Indian Inst Sci Supercomp Educ & Res Ctr Bangalore 560012 Karnataka India

The Morse-Smale complex is a useful topological data structure for the analysis and visualization of scalar data. This paper describes an algorithm that processes all mesh elements of the domain in parallel to compute the Morse-Smale complex of large 2D datasets at interactive speeds. We employ a reformulation of the Morse-Smale complex using Forman's Discrete Morse Theory and achieve scalability by computing the discrete gradient using local accesses only. We also introduce a novel approach to merge gradient paths that ensures accurate geometry of the computed complex. We demonstrate that our algorithm performs well on both multicore environments and on massively parallel architectures such as the GPU.

关键词： Topology-based methods discrete Morse theory large datasets gradient pairs multicore 2D scalar functions

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A PC cluster system for simultaneous interactive volumetric modeling and visualization 03

A PC cluster system for simultaneous interactive volumetric ...

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ieee symposium on parallel and large-data visualization and graphics

作者： Muraki, S Lum, EB Ma, KL Ogata, M Liu, XZ AIST Japan University of California Davis Mitsubishi Precision Co. Ltd. Japan

ISBN: (纸本)078038122X

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. In this paper, 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.

关键词： graphics hardware PC clusters parallel volume rendering reaction-diffusion patterns visual computing volume graphics volume modeling

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Flying Edges: A High-Performance Scalable Isocontouring Algorithm 5

Flying Edges: A High-Performance Scalable Isocontouring Algo...

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ieee 5th symposium on large data Analysis and visualization (LDAV)

作者： Schroeder, William Maynard, Rob Geveci, Berk Kitware Inc Clifton Pk NY 12065 USA

ISBN: (纸本)9781467385176

Isocontouring remains one of the most widely used visualization techniques. While a plethora of important contouring algorithms have been developed over the last few decades, many were created prior to the advent of ubiquitous parallel computing systems. With the emergence of large data and parallel architectures, a rethinking of isocontouring and other visualization algorithms is necessary to take full advantage of modern computing hardware. To this end we have developed a high-performance isocontouring algorithm for structured data that is designed to be inherently scalable. Processing is performed completely independently along edges over multiple passes. This novel algorithm also employs computational trimming based on geometric reasoning to eliminate unnecessary computation, and removes the parallel bottleneck due to coincident point merging. As a result the algorithm performs well in serial or parallel execution, and supports heterogeneous parallel computation combining data parallel and shared memory approaches. Further it is capable of processing data too large to fit entirely inside GPU memory, does not suffer additional costs due to preprocessing and search structures, and is the fastest non-preprocessed isocontouring algorithm of which we are aware on shared memory, multicore systems. The software is currently available under a permissive, open source licence in the VTK visualization system.

关键词： I.3.1 [Computing Methodologies]: Computer graphics ??? parallel processing I.3.5 [Computing Methodologies]: Computational Geometry and Object Modeling ??? Geometric algorithms Flying shared memory spatial reasoning algorithms parallel execution Scalability parallel PROCESSING (COMPUTERS) Plethora Serial Publications edges Computer hardware

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Ray casting architectures for volume visualization

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 1999年第3期5卷 210-223页

作者： Ray, H Pfister, H Silver, D Cook, TA Rutgers State Univ Dept Elect & Comp Engn New Brunswick NJ 08903 USA Mitsubishi Electr Corp Res Cambridge MA 02139 USA Rutgers State Univ Dept Elect & Comp Engn Piscataway NJ 08855 USA Improv Syst Inc Beverly MA 01915 USA

Real-time visualization of large volume datasets demands high performance computation, pushing the storage, processing, and data communication requirements to the limits of current technology. General purpose parallel processors have been used to visualize moderate size datasets at interactive frame rates;however, the cost and size of these supercomputers inhibits the widespread use for real-time visualization. This paper surveys several special purpose architectures that seek to render volumes at interactive rates. These specialized visualization accelerators have cost, performance, and size advantages over parallel processors. All architectures implement ray casting using parallel and pipelined hardware. We introduce a new metric that normalizes performance to compare these architectures. The architectures included in this survey are VOGUE, VIRIM, Array Based Ray Casting, EM-Cube, and VIZARD II. We also discuss future applications of special purpose accelerators.

关键词： volume rendering interactive ray casting parallel architecture VOGUE VIRIM array based ray casting EM-Cube VIZARD II

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In Situ visualization for large-Scale Combustion Simulations

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ieee COMPUTER graphics AND APPLICATIONS 2010年第3期30卷 45-57页

作者： Yu, Hongfeng Wang, Chaoli Grout, Ray W. Chen, Jacqueline H. Ma, Kwan-Liu Sandia Natl Labs Livermore CA 94550 USA Michigan Technol Univ Houghton MI 49931 USA Univ Calif Davis Grad Grp Comp Sci Davis CA 95616 USA

The article focuses in situ visualization as a scalable way for scientists to view the data that their large-scale combustion simulations generate. The challenges of in situ visualization are discussed, such as parallel rendering which includes volume and particle rendering and the integration of the two. Also included are direct numerical simulation, simulation-time visualization, and parallel image compositing.

关键词： visualization SUPERCOMPUTERS parallel processing (Electronic computers) HIGH performance computing COMPUTERS

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Proxy Graph: Visual Quality Metrics of Big Graph Sampling

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2017年第6期23卷 1600-1611页

作者： Quan Hoang Nguyen Hong, Seok-Hee Eades, Peter Meidiana, Amyra Univ Sydney Sch Informat Technol Camperdown NSW 2006 Australia

data sampling has been extensively studied for large scale graph mining. Many analyses and tasks become more efficient when performed on graph samples of much smaller size. The use of proxy objects is common in software engineering for analysis and interaction with heavy objects or systems. In this paper, we coin the term 'proxy graph' and empirically investigate how well a proxy graph visualization can represent a big graph. Our investigation focuses on proxy graphs obtained by sampling;this is one of the most common proxy approaches. Despite the plethora of data sampling studies, this is the first evaluation of sampling in the context of graph visualization. For an objective evaluation, we propose a new family of quality metrics for visual quality of proxy graphs. Our experiments cover popular sampling techniques. Our experimental results lead to guidelines for using sampling-based proxy graphs in visualization.

关键词： Graph visualization graph sampling proxy graph quality metrics

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parallel volume rendering on a single-chip SIMD architecture

Parallel volume rendering on a single-chip SIMD architecture

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ieee symposium on parallel and large-data visualization and graphics

作者： Meissner, M Grimm, S Strasser, W Packer, J Latimer, D Univ Tubingen WSI GRIS D-72076 Tubingen Germany

ISBN: (纸本)0780372239

Volume rendering has great potential for parallelization due to the tremendous number of computations necessary. Besides the enormous computational power needed, the memory interface is usually of crucial importance and frequently the bottleneck. This paper presents an implementation of a parallel ray casting algorithm for orthogonal projections on a new single-chip SIMD architecture. Concurrent processing of rays is scheduled such that redundant memory accesses of the individual processing elements can be detected by the channel controller. Hence, data can be read efficiently in block-wise manner. For improved image quality, a permutation of the Shear-Warp algorithm with trilinear interpolation is used. The steps of the ray casting algorithm are carefully mapped onto the architecture avoiding expensive floating point operation, giving superior performance over previously reported results. A detailed analysis illustrates the timing of the individual computations and memory accesses, identifying the costliest parts of the implementation.

关键词： volume rendering ray casting parallel processing

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parallel sets: Interactive exploration and visual analysis of categorical data

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2006年第4期12卷 558-568页

作者： Kosara, R Bendix, F Hauser, H Univ N Carolina Dept Comp Sci Charlotte NC 28223 USA VRVis Res Ctr A-1220 Vienna Austria

Categorical data dimensions appear in many real-world data sets, but few visualization methods exist that properly deal with them. parallel Sets are a new method for the visualization and interactive exploration of categorical data that shows data frequencies instead of the individual data points. The method is based on the axis layout of parallel coordinates, with boxes representing the categories and parallelograms between the axes showing the relations between categories. In addition to the visual representation, we designed a rich set of interactions. parallel Sets allow the user to interactively remap the data to new categorizations and, thus, to consider more data dimensions during exploration and analysis than usually possible. At the same time, a metalevel, semantic representation of the data is built. Common procedures, like building the cross product of two or more dimensions, can be performed automatically, thus complementing the interactive visualization. We demonstrate parallel Sets by analyzing a large CRM data set, as well as investigating housing data from two US states.

关键词： information visualization interaction nominal data categorical data multivariate data

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Comparing Binary-Swap Algorithms for Odd Factors of Processes 8

Comparing Binary-Swap Algorithms for Odd Factors of Processe...

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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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large-Scale Cinematic visualization Using Universal Scene Description 9

Large-Scale Cinematic Visualization Using Universal Scene De...

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9th ieee symposium on large data Analysis and visualization (LDAV)

作者： Bolstad, Mark A. Sandia Natl Labs Livermore CA 94550 USA

ISBN: (纸本)9781728126050

Universal Scene Description (USD) is the core of Pixar Animation Studios graphics and rendering pipeline. Released as open source in 2016, USD provides for the interchange of elemental assets (e.g. models), but additionally enables assembly and organization of any number of assets into higher level concepts, such as scenes or shots. These assets can be non-destructively edited or modified through layering that can then be transmitted between applications. Exporting scientific simulations through the USD API allows access to a wide range of tools for creating cinematic visualizations or for viewing scientific simulations in an augmented/virtual reality environment.

关键词： Human-centered computing visualization visualization systems and tools visualization toolkits Computing methodologies Computer graphics graphics systems and interfaces graphics file formats

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