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Hybrid parallelism for Volume Rendering on large-, Multi-, and Many- Core Systems

ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2012年第1期18卷 17-29页

作者： Howison, Mark Bethel, E. Wes Childs, Hank Brown Univ Ctr Computat & Visualizat Providence RI 02912 USA Univ Calif Berkeley Lawrence Berkeley Lab Visualizat Grp Berkeley CA 94720 USA

With the computing industry trending toward multi- and many- core processors, we study how a standard visualization algorithm, raycasting volume rendering, can benefit from a hybrid parallelism approach. Hybrid parallelism provides the best of both worlds: using distributed-memory parallelism across a large numbers of nodes increases available FLOPs and memory, while exploiting shared-memory parallelism among the cores within each node ensures that each node performs its portion of the larger calculation as efficiently as possible. We demonstrate results from weak and strong scaling studies, at levels of concurrency ranging up to 216,000, and with data sets as large as 12.2 trillion cells. The greatest benefit from hybrid parallelism lies in the communication portion of the algorithm, the dominant cost at higher levels of concurrency. We show that reducing the number of participants with a hybrid approach significantly improves performance.

关键词： Volume visualization parallel processing

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Enabling automatic clutter reduction in parallel coordinate plots

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2006年第5期12卷 717-723页

作者： Ellis, Geoffrey Dix, Alan Univ Lancaster Lancaster LA1 4YW England

We have previously shown that random sampling is an effective clutter reduction technique and that a sampling lens can facilitate focus+context viewing of particular regions. This demands an efficient method of estimating the overlap or occlusion of large numbers of intersecting lines in order to automatically adjust the sampling rate within the lens. This paper proposes several ways for measuring occlusion in parallel coordinate plots. An empirical study into the accuracy and efficiency of the occlusion measures show that a probabilistic approach combined with a 'binning' technique is very fast and yet approaches the accuracy of the more expensive 'true' complete measurement.

关键词： sampling random sampling lens clutter occlusion density reduction overplotting information visualisation parallel coordinates

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Visual data Analysis as an Integral Part of Environmental Management

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2012年第12期18卷 2088-2094页

作者： Meyer, Joerg Bethel, E. Wes Horsman, Jennifer L. Hubbard, Susan S. Krishnan, Harinarayan Romosan, Alexandru Keating, Elizabeth H. Monroe, Laura Strelitz, Richard Moore, Phil Taylor, Glenn Torkian, Ben Johnson, Timothy C. Gorton, Ian Lawrence Berkeley Natl Lab Berkeley CA USA Los Alamos Natl Lab Los Alamos NM 87545 USA Pacific NW Natl Lab Richland WA 99352 USA

The U.S. Department of Energy's (DOE) Office of Environmental Management (DOE/EM) currently supports an effort to understand and predict the fate of nuclear contaminants and their transport in natural and engineered systems. Geologists, hydrologists, physicists and computer scientists are working together to create models of existing nuclear waste sites, to simulate their behavior and to extrapolate it into the future. We use visualization as an integral part in each step of this process. In the first step, visualization is used to verify model setup and to estimate critical parameters. High-performance computing simulations of contaminant transport produces massive amounts of data, which is then analyzed using visualization software specifically designed for parallel processing of large amounts of structured and unstructured data. Finally, simulation results are validated by comparing simulation results to measured current and historical field data. We describe in this article how visual analysis is used as an integral part of the decision-making process in the planning of ongoing and future treatment options for the contaminated nuclear waste sites. Lessons learned from visually analyzing our large-scale simulation runs will also have an impact on deciding on treatment measures for other contaminated sites.

关键词： Visual analytics high-performance computing data management parallel rendering environmental management

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Melange: Space Folding for Visual Exploration

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2010年第3期16卷 468-483页

作者： Elmqvist, Niklas Riche, Yann Henry-Riche, Nathalie Fekete, Jean-Daniel Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA Microsoft Res Redmond WA 98052 USA Univ Paris 11 LRI INRIA Saclay F-91405 Orsay France

Navigating in large geometric spaces-such as maps, social networks, or long documents-typically requires a sequence of pan and zoom actions. However, this strategy is often ineffective and cumbersome, especially when trying to study and compare several distant objects. We propose a new distortion technique that folds the intervening space to guarantee visibility of multiple focus regions. The folds themselves show contextual information and support unfolding and paging interactions. We conducted a study comparing the space-folding technique to existing approaches and found that participants performed significantly better with the new technique. We also describe how to implement this distortion technique and give an in-depth case study on how to apply it to the visualization of large-scale 1D time-series data.

关键词： Interaction visualization navigation exploration folding split screen space distortion focus plus context

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An Application-Aware data Replacement Policy for Interactive large-Scale Scientific visualization 31

An Application-Aware Data Replacement Policy for Interactive...

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31st ieee International parallel and Distributed Processing symposium Workshops (IPDPS)

作者： Yu, Lina Yu, Hongfeng Jiang, Hong Wang, Jun Univ Nebraska Lincoln NE 68583 USA Univ Texas Arlington Arlington TX 76019 USA Univ Iowa Iowa City IA USA

ISBN: (纸本)9780769561493

The unprecedented amounts of data generated from large scientific simulations impose a grand challenge in data analytics, and I/O simply becomes a major performance bottleneck. To address this challenge, we present an application-aware I/O optimization technique in support of interactive large-scale scientific visualization. We partition a scientific data into blocks, and carefully place data blocks in a memory hierarchy according to a characterization of data access patterns of user visualization operations. We conduct an empirical study to explore the parameter space to derive optimal solutions. We use real-world large-scale simulation datasets to demonstrate the effectiveness of our approach.

关键词： I/O optimization scientific visualization data replacement large-scale data

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A study of I/O methods for parallel visualization of large-scale data

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parallel COMPUTING 2005年第2期31卷 167-183页

作者： Yu, HF Ma, KL Univ Calif Davis Dept Comp Sci Davis CA 95616 USA

This paper presents two parallel I/O methods for the visualization of time-varying volume data in a high-performance computing environment. We discuss the interplay between the parallel renderer, I/O strategy, and file system, and show the results of our study on the performance of the I/O strategies with and without MPI parallel I/O support. The targeted application is earthquake modeling using a large 3D unstructured mesh consisting of one hundred millions cells. Our test results on the HP/Cornpaq AlphaServer operated at the Pittsburgh Supercomputing Center demonstrate that the I/O methods effectively remove the I/O bottlenecks commonly present in time-varying data visualization, and therefore help significantly lower interfrarne delay. This high-performance visualization solution allows scientists to explore their data in the temporal, spatial, and visualization domains at high resolution. Such new explorability, likely not presently available to most computational science groups, will help lead to many new insights into the modeled physical and chemical processes. (c) 2005 Elsevier B.V. All rights reserved.

关键词： high-performance computing massively parallel supercomputing MPI scientific visualization parallel I/O parallel rendering time-varying data volume rendering

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parallel sets: Interactive exploration and visual analysis of categorical data

Parallel sets: Interactive exploration and visual analysis o...

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ieee symposium on Information visualization (InfoVis 05)

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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parallel stream surface computation for large data sets

Parallel stream surface computation for large data sets

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2nd symposium on large-Scale data Analysis and visualization, LDAV 2012

作者： Camp, David Childs, Hank Garth, Christoph Pugmire, David Joy, Kenneth I. Lawrence Berkeley National Laboratory University of California Davis CA United States University of Kaiserslautern Germany Oak Ridge National Laboratory United States University of California Davis CA United States

ISBN: (纸本)9781467347334

parallel stream surface calculation, while highly related to other particle advection-based techniques such as streamlines, has its own unique characteristics that merit independent study. Specifically, stream surfaces require new integral curves to be added continuously during execution to ensure surface quality and accuracy;performance can be improved by specifically accounting for these additional particles. We present an algorithm for generating stream surfaces in a distributed-memory parallel setting. The algorithm incorporates multiple schemes for parallelizing particle advection and we study which schemes work best. Further, we explore speculative calculation and how it can improve overall performance. In total, this study informs the efficient calculation of stream surfaces in parallel for large data sets, based on existing integral curve functionality. © 2012 ieee.

关键词： parallel programming

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parallel accelerated isocontouring for out-of-core visualization

Parallel accelerated isocontouring for out-of-core visualiza...

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1999 ieee symposium on parallel visualization and graphics, PVGS 1999

作者： Bajaj, C.L. Pascucci, V. Thompson, D. Zhang, X.Y. Department of Computer Sciences and TICAM University of Texas AustinTX78733 United States

ISBN: (纸本)1581132379

In this paper we introduce a scheme for static analysis that allows us to partition large geometric datasets at multiple levels of granularity to achieve both load balancing in parallel computations and minimal access to secondary memory in out-of-core computations. The idea is illustrated and fully exploited for the case of isosurface extraction, but extendible to a class of algorithms based on a small set of parameters and for which an appropriate static analysis can be performed.

关键词： Static analysis

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Meta parallel coordinates for visualizing features in large, high-dimensional, time-varying data

Meta parallel coordinates for visualizing features in large,...

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2nd symposium on large-Scale data Analysis and visualization, LDAV 2012

作者： Dasgupta, Aritra Kosara, Robert Gosink, Luke UNC Charlotte United States Pacific Northwest National Lab. United States

ISBN: (纸本)9781467347334

Managing computational complexity and designing effective visual representations are two important challenges for the visualization of large, complex, high-dimensional datasets. parallel coordinates are an effective technique for visualizing high-dimensional data, but do not scale well to very large datasets. The addition of the temporal dimension leads to more uncertainty due to clutter on screen. Consequently, this poses a significant challenge for visually finding trends and patterns that maximize insight about the underlying time-varying properties of the data. To address these problems, we present meta parallel coordinates, a parallel coordinates display that is guided by perceptually motivated visual metrics. These metrics describe the visual structures typically found in parallel coordinates and thus aid the user's analysis by providing meaningful views of the data. Since they are computed in screen space, our metrics are computationally more efficient than data-based metrics. Our choice of metrics is driven by the different analytical tasks that a user typically wants to perform with time-varying multivariate data. In particular, we have worked with domain scientists who performed simulations of bioremediation experiments, and use their data and results to demonstrate the usefulness of our approach. © 2012 ieee.

关键词： Bioremediation

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