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2013 3rd ieee symposium on large-Scale data Analysis and visualization, LDAV 2013

作者： Lorendeau, Benjamin Fournier, Yvan Ribes, Alejandro University of Bordeaux 1 France Electricité de France RandD France

ISBN: (纸本)9781479916597

Numerical simulations using supercomputers are producing an increasingly larger volume of data to be visualized. In this context, Catalyst is a prototype In-Situ visualization library developed by Kitware to help reduce the data post-treatment overhead. On the other side, Code Saturne is a Computational Fluid Dynamics code used at Eléctricité de France (EDF), one of the biggest electricity producers in Europe, for its large scale numerical simulations. In this article we present a study case where Catalyst is integrated into Code Saturne. We evaluate the feasibility and performance of this integration by running two test cases in one of our corporate supercomputers. © 2013 ieee.

关键词： Computational fluid dynamics

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A multiresolution volume rendering framework for large-scale time-varying data visualization

A multiresolution volume rendering framework for large-scale...

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Fourth International Workshop on Volume graphics 2005

作者： Wang, Chaoli Gao, Jinzhu Li, Liya Shen, Han-Wei Ohio State University Columbus OH 43210 United States Oak Ridge National Laboratory Oak Ridge TN 37831 United States

ISBN: (纸本)3905673266

We present a new parallel multiresolution volume rendering framework for large-scale time-varying data visualization using the wavelet-based time-space partitioning (WTSP) tree. Utilizing the wavelet transform, a large-scale time-varying data set is converted into a space-time multiresolution data hierarchy, and is stored in a time-space partitioning (TSP) tree. To eliminate the parent-child data dependency for reconstruction and achieve toad-balanced rendering, we design an algorithm to partition the WTSP tree and distribute the wavelet-compressed data along hierarchical space-filling curves with error-guided bucketization. At run time, the WTSP tree is traversed according to the user-specified time step and tolerances of both spatial and temporal errors. data blocks of different spatio-temporal resolutions are reconstructed and rendered to compose the final image in parallel. We demonstrate that our algorithm can reduce the run-time communication cost to a minimum and ensure a well-balanced workload among processors when visualizing gigabytes of time-varying data on a PC cluster. © The Eurographics Association 2005.

关键词： Wavelet transforms

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Hierarchical pixel bar charts

Hierarchical pixel bar charts

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7th ieee symposium on Information visualization (INFOVIS 2001)

作者： Keim, DA Hao, MC Dayal, U AT&T Corp Res Florham Pk NJ USA Univ Constance D-7750 Constance Germany Hewlett Packard Res Labs Palo Alto CA USA

Simple presentation graphics are intuitive and easy-to-use, but only show highly aggregated data. Bar charts, for example, only show a rather small number of data values and x-y-plots often have a high degree of overlap. Presentation techniques are often chosen depending on the considered data type-bar charts, for example, are used for categorical data and x-y plots are used for numerical data. In this article, we propose a combination of traditional bar charts and x-y-plots, which allows the visualization of large amounts of data with categorical and numerical data. The categorical data dimensions are used for the partitioning into the bars and the numerical data dimensions are used for the ordering arrangement within the bars. The basic idea is to use the pixels within the bars to present the detailed information of the data records. Our so-called pixel bar charts retain the intuitiveness of traditional bar charts while applying the principle of x-y charts within the bars. In many applications, a natural hierarchy is defined on the categorical data dimensions such as time, region, or product type. In hierarchical pixel bar charts, the hierarchy is exploited to split the bars for selected portions of the hierarchy. Our application to a number of real-world e-business and Web services data sets shows the wide applicability and usefulness of our new idea.

关键词： information visualization multidimensional data visualization visual data exploration and data mining very large multiattributes data sets hierarchical visualization

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Scalable Lagrangian-based Attribute Space Projection for Multivariate Unsteady Flow data

Scalable Lagrangian-based Attribute Space Projection for Mul...

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ieee Pacific visualization symposium (PacificVis)

作者： Guo, Hanqi Hong, Fan Shu, Qingya Zhang, Jiang Huang, Jian Yuan, Xiaoru Peking Univ Minist Educ Key Lab Machine Percept Beijing Peoples R China Peking Univ Sch EECS Beijing Peoples R China Peking Univ Ctr Computat Sci & Engn Beijing Peoples R China Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN USA

ISBN: (纸本)9781479928736

In this paper, we present a novel scalable approach for visualizing multivariate unsteady flow data with Lagrangian-based Attribute Space Projection (LASP). The distances between spatiotemporal samples are evaluated by their attribute values along the advection directions in the flow field. The massive samples are then projected into 2D screen space for feature identification and selection. A hybrid parallel system, which tightly integrates a MapReduce-style particle tracer with a scalable algorithm for the projection, is designed to support the large scale analysis. Results show that the proposed methods and system are capable of visualizing features in the unsteady flow, which couples multivariate analysis of vector and scalar attributes with projection.

关键词： Flow visualization attribute space projection parallel processing

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A Visual Analytics Framework for Reviewing Streaming Performance data 13

A Visual Analytics Framework for Reviewing Streaming Perform...

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ieee Pacific visualization symposium (PacificVis)

作者： Kesavan, Suraj P. Fujiwara, Takanori Li, Jianping Kelvin Ross, Caitlin Mubarak, Misbah Carothers, Christopher D. Ross, Robert B. Ma, Kwan-Liu Univ Calif Davis Davis CA 95616 USA Rensselaer Polytech Inst Troy NY 12181 USA Argonne Natl Lab Argonne IL 60439 USA

ISBN: (数字)9781728156972

ISBN: (纸本)9781728156972

Understanding and tuning the performance of extreme-scale parallel computing systems demands a streaming approach due to the computational cost of applying offline algorithms to vast amounts of performance log data. Analyzing large streaming data is challenging because the rate of receiving data and limited time to comprehend data make it difficult for the analysts to sufficiently examine the data without missing important changes or patterns. To support streaming data analysis, we introduce a visual analytic framework comprising of three modules: data management, analysis, and interactive visualization. The data management module collects various computing and communication performance metrics from the monitored system using streaming data processing techniques and feeds the data to the other two modules. The analysis module automatically identifies important changes and patterns at the required latency. In particular, we introduce a set of online and progressive analysis methods for not only controlling the computational costs but also helping analysts better follow the critical aspects of the analysis results. Finally, the interactive visualization module provides the analysts with a coherent view of the changes and patterns in the continuously captured performance data. Through a multi-faceted case study on performance analysis of parallel discrete-event simulation, we demonstrate the effectiveness of our framework for identifying bottlenecks and locating outliers.

关键词： Human-centered computing visualization visualization application domains Visual analytics

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Application of Pareto Sets in Quality Control of Series Production in Car Manufacturing 8

Application of Pareto Sets in Quality Control of Series Prod...

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ieee Pacific visualization symposium (PacificVis)

作者： Huettenberger, Lars Feige, Nils Ebert, Achim Garth, Christoph TU Kaiserslautern Kaiserslautern Germany

ISBN: (纸本)9781467368797

In car manufacturing, quality management and control are important parts of the series process. In series production, many parts are controlled in various ways in some or all stages of assembly. While tactile measurements are mostly restricted to the points on an inspection plan, this restriction does not apply to optical measurements. We propose a method based on the theory of Pareto sets (multivariate topological analysis) to cope with the large amount of data produced by optical measurements and to find points of interest on the measured surface in addition to the inspection plan. We describe a method which automatically detects areas of systematic errors on a component and visualizes them on the triangulated surface. The visualization can help experts to decide, whether a detected feature is severe enough to be added to the inspection plan.

关键词： I.3.8 [Computer Methodologies]: Computer graphics—Application J.6 [Computer Applications]: Computeraided Engineering INSPECTION PLANS batch production Optical variables measurement Quality Control Automobile manufacture Cars Carina Quality management measurement surface visualization Systematic errors SETTING

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Utilizing Many-Core Accelerators for Halo and Center Finding within a Cosmology Simulation 5

Utilizing Many-Core Accelerators for Halo and Center Finding...

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

作者： Sewell, Christopher Lo, Li-ta Heitmann, Katrin Habib, Salman Ahrens, James Los Alamos Natl Lab Los Alamos NM 87545 USA Argonne Natl Lab Argonne IL 60439 USA

ISBN: (纸本)9781467385176

Efficiently finding and computing statistics about "halos" (regions of high density) are essential analysis steps for N-body cosmology simulations. However, in state-of-the-art simulation codes, these analysis operators do not currently take advantage of the shared-memory data-parallelism available on multi-core and many-core architectures. The Hybrid / Hardware Accelerated Cosmology Code (HACC) is designed as an MPI+X code, but the analysis operators are parallelized only among MPI ranks, because of the difficulty in porting different X implementations (e.g., OpenMP, CUDA) across all architectures on which it is run. In this paper, we present portable data-parallel algorithms for several variations of halo finding and halo center finding algorithms. These are implemented with the PISTON component of the VTK-m framework, which uses Nvidia's Thrust library to construct data-parallel algorithms that allow a single implementation to be compiled to multiple backends to target a variety of multi-core and many-core architectures. Finally, we compare the performance of our halo and center finding algorithms against the original HACC implementations on the Moonlight, Stampede, and Titan supercomputers. The portability of Thrust allowed the same code to run efficiently on each of these architectures. On Titan, the performance improvements using our code have enabled halo analysis to be performed on a very large data set (81923 particles across 16,384 nodes of Titan) for which analysis using only the existing CPU algorithms was not feasible.

关键词： D.1.3 [Software]: Programming Techniques ??? [Concurrent Prgm.] haloes Titan ARCHITECTURE Codes Cosmology FINDINGS thrust Portability algorithms data parallel

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Toward Localized Topological data Structures: Querying the Forest for the Tree

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2020年第1期26卷 173-183页

作者： Klacansky, Pavol Gyulassy, Attila Bremer, Peer-Timo Pascucci, Valerio Univ Utah Sci Comp & Imaging Inst Salt Lake City UT 84112 USA Lawrence Livermore Natl Lab Livermore CA USA

Topological approaches to data analysis can answer complex questions about the number, connectivity, and scale of intrinsic features in scalar data. However, the global nature of many topological structures makes their computation challenging at scale, and thus often limits the size of data that can be processed. One key quality to achieving scalability and performance on modern architectures is data locality, i.e., a process operates on data that resides in a nearby memory system, avoiding frequent jumps in data access patterns. From this perspective, topological computations are particularly challenging because the implied data structures represent features that can span the entire data set, often requiring a global traversal phase that limits their scalability. Traditionally, expensive preprocessing is considered an acceptable trade-off as it accelerates all subsequent queries. Most published use cases, however, explore only a fraction of all possible queries, most often those returning small, local features. In these cases, much of the global information is not utilized, yet computing it dominates the overall response time. We address this challenge for merge trees, one of the most commonly used topological structures. In particular, we propose an alternative representation, the merge forest a collection of local trees corresponding to regions in a domain decomposition. Local trees are connected by a bridge set that allows us to recover any necessary global information at query time. The resulting system couples (i) a preprocessing that scales linearly in practice with (ii) fast runtime queries that provide the same functionality as traditional queries of a global merge tree. We test the scalability of our approach on a shared-memory parallel computer and demonstrate how data structure locality enables the analysis of large data with an order of magnitude performance improvement over the status quo. Furthermore, a merge forest reduces the memory overhead compare

关键词： Merge tree parallel computation topology

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Dual multiresolution HyperSlice for multivariate data visualization

Dual multiresolution HyperSlice for multivariate data visual...

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Proceedings of the 1996 ieee symposium on Information visualization

作者： Wong, Pak Chung Crabb, Andrew H. Bergeron, R.Daniel Univ of New Hampshire Durham United States

We present a new multiresolution visualization design which allows a user to control the physical data resolution as well as the logical display resolution of multivariate data. A system prototype is described which uses the HyperSlice representation. The notion of space projection in multivariate data is introduced. This process is coupled with wavelets to form a powerful tool for very large data visualization.

关键词： Computer graphics

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Proceedings - ieee symposium on Information visualization, INFO VIS

Proceedings - IEEE Symposium on Information Visualization, I...

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ieee symposium on Information visualization, INFOVIS 2002

ISBN: (纸本)076951751X

The proceedings contain 23 papers. The topics discussed include: multiscale visualization using data cubes;visualization schemas for flexible information visualization;building a visual database for example-based graphics generation;efficient cartogram generation: a comparison;visualizing data with bounded uncertainty;graphical encoding for information visualization: an empirical study;the illusion of perceived metric 3D structure;process visualization with levels of detail;case study: visualizing sets of evolutionary trees;InterRing: an interactive tool for visually navigating and manipulating hierarchical structures;beamtrees: compact visualization of large hierarchies;visualizing biosequence data using texture mapping;and arc diagrams: visualizing structure in strings.

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