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检索条件"任意字段=2013 3rd IEEE Symposium on Large-Scale Data Analysis and Visualization, LDAV 2013"

共 28 条记录，以下是1-10 订阅

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Visual analysis on online display advertising data

Visual analysis on online display advertising data

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2013 3rd ieee symposium on large-scale data analysis and visualization, ldav 2013

作者： Huang, Ling Genome from Yahoo United States

ISBN: (纸本)9781479916597

In recent years online display advertising has grown at a rapid pace. Genome from Yahoo! is the big data buying solution for online display advertising. The goal of our platform is to identify the best opportunity to display an ad to a user who is most likely to take a desired action. Our system contains websites which are visited by several million users per day. The number of attributes related to user events is also of the order of several thousand. Visual analysis has emerged as a powerful technique to facilitate demonstrating data, filtering extreme cases and outliers, exploiting data details, and identifying data analysis tasks. With respect to large-scale online data, the paper presents some use cases on visual analysis at Genome from Yahoo! © 2013 ieee.

关键词： Big data

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ieee symposium on large data analysis and visualization 2013, ldav 2013 - Proceedings

IEEE Symposium on Large Data Analysis and Visualization 2013...

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2013 3rd ieee symposium on large-scale data analysis and visualization, ldav 2013

ISBN: (纸本)9781479916597

The proceedings contain 23 papers. The topics discussed include: distributed parallel particle advection using work requesting;a scalable algorithm for single-linkage hierarchical clustering on distributed-memory architectures;portable data-parallel visualization and analysis in distributed memory environments;efficient parallel volume rendering of large-scale adaptive mesh refinement data;visualizing large-scale atomistic simulations in ultra-resolution immersive environments;a provably-robust sampling method for generating colormaps of large data;trelliscope: a system for detailed visualization in the deep analysis of large complex data;filtering edge for exploration of large graphs;proper orthogonal decomposition based parallel compression for visualizing big data on the K Computer;and visual analysis on online display advertising data.

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In-Situ visualization in fluid mechanics using Catalyst: A case study for Code Saturne

In-Situ visualization in fluid mechanics using Catalyst: A c...

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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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Distributed parallel particle advection using work requesting

Distributed parallel particle advection using work requestin...

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2013 3rd ieee symposium on large-scale data analysis and visualization, ldav 2013

作者： Muller, Cornelius Camp, David Hentschel, Bernd Garth, Christoph University of Kaiserslautern Germany Lawrence Berkeley National Laboratory United States RWTH Aachen University Germany

ISBN: (纸本)9781479916597

Particle advection is an important vector field visualization technique that is difficult to apply to very large data sets in a distributed setting due to scalability limitations in existing algorithms. In this paper, we report on several experiments using work requesting dynamic scheduling which achieves balanced work distribution on arbitrary problems with minimal communication overhead. We present a corresponding prototype implementation, provide and analyze benchmark results, and compare our results to an existing algorithm. © 2013 ieee.

关键词： data visualization

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Comparative case study between D3 & Highcharts on Lustre metadata visualization

Comparative case study between D3 & Highcharts on Lustre met...

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2013 3rd ieee symposium on large-scale data analysis and visualization, ldav 2013

作者： Eltayeby, Omar John, Dwayne Patel, Pragnesh Simmerman, Scott Clark Atlanta University United States National Institute for Computational Sciences United States

ISBN: (纸本)9781479916597

One of the challenging tasks in visual analytics is to target clustered time-series data sets, since it is important for data analysts to discover patterns changing over time while keeping their focus on particular subsets. A web-based application to monitor the Lustre file system for system administrators and operation teams has been developed using D3 and Highcharts. This application is a use case to compare those JavaScript libraries demonstrating the differences in capabilities of using them. The goal of this application is to provide time-series visuals of the Remote Procedure Calls (RPCs) and storage patterns of users on Kraken, a University of Tennessee High Performance Computing (HPC) resource in Oak Ridge National Laboratory (ORNL). © 2013 ieee.

关键词： visualization

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visualization of multivariate dark matter halos in cosmology simulations

Visualization of multivariate dark matter halos in cosmology...

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2013 3rd ieee symposium on large-scale data analysis and visualization, ldav 2013

作者： Takle, Jay Silver, Deborah Kovacs, Eve Heitmann, Katrin Dept. of Electrical and Computer Engineering Rutgers University United States High Energy Physics Division Argonne National Laboratory United States

ISBN: (纸本)9781479916597

In this poster, we present a new approach to visualize multivariate dark matter halos representing the spheroid part of galaxies, the disk part of galaxies, black holes and the halo itself. The data being visualized here is an end result of tracking the evolution of cosmic structures called dark matter halos in cosmological simulation and evaluating the formation and evolution of galaxies within. Cosmologists have traditionally visualized individual galaxies in the form of two dimensional density maps, graphs and parallel coordinates. We introduce a new way of mapping multiple parameters of dark matter halos to a halo-icon. This allows the scientist to view all of the parameters associated with the dark matter halos in one visualization. © 2013 ieee.

关键词： Galaxies

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An analysis of scalable GPU-based ray-guided volume rendering

An analysis of scalable GPU-based ray-guided volume renderin...

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2013 3rd ieee symposium on large-scale data analysis and visualization, ldav 2013

作者： Fogal, Thomas Schiewe, Alexander Kruger, Jens HPC Group Duisburg-Essen SCI Germany HPC Group Duisburg-Essen Intel VCI Germany

ISBN: (纸本)9781479916597

Volume rendering continues to be a critical method for analyzing large-scale scalar fields, in disciplines as diverse as biomedical engineering and computational fluid dynamics. Commodity desktop hardware has struggled to keep pace with data size increases, challenging modern visualization software to deliver responsive interactions for O(N3) algorithms such as volume rendering. We target the data type common in these domains: regularly-structured data. In this work, we demonstrate that the major limitation of most volume rendering approaches is their inability to switch the data sampling rate (and thus data size) quickly. Using a volume renderer inspired by recent work, we demonstrate that the actual amount of visualizable data for a scene is typically bound considerably lower than the memory available on a commodity GPU. Our instrumented renderer is used to investigate design decisions typically swept under the rug in volume rendering literature. The renderer is freely available, with binaries for all major platforms as well as full source code, to encourage reproduction and comparison with future research. © 2013 ieee.

关键词： Volume rendering

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Efficient parallel volume rendering of large-scale adaptive mesh refinement data

Efficient parallel volume rendering of large-scale adaptive ...

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2013 3rd ieee symposium on large-scale data analysis and visualization, ldav 2013

作者： Leaf, Nick Vishwanath, Venkatram Insley, Joseph Hereld, Mark Papka, Michael E. Ma, Kwan-Liu University of California Davis United States Argonne National Laboratory United States Northern Illinois University United States

ISBN: (纸本)9781479916597

Adaptive Mesh Refinement is a popular approach for allocating scarce computing resources to the most important portions of the simulation domain. This approach implies spatial compression and the large simulation sizes which necessitate it. We present a novel, cluster- and GPU-parallel rendering scheme for AMR data, which is built on previous work in the GPU ray casting of AMR data. Our approach utilizes the existing AMR structure to subdivide the problem into convexly-bounded chunks and perform static load-balancing. We take advantage of data locality within chunks to interpolate directly between blocks without the need to store ghost cells on the interior boundaries. We also present a novel block decomposition method, and analyze its performance against two alternative methods. Finally, we examine the interactivity of our renderer for multiple datasets, and consider its scalability across a large number of GPUs. © 2013 ieee.

关键词： Volume rendering

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Damaris/Viz: A nonintrusive, adaptable and user-friendly in situ visualization framework

Damaris/Viz: A nonintrusive, adaptable and user-friendly in ...

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2013 3rd ieee symposium on large-scale data analysis and visualization, ldav 2013

作者： Dorier, Matthieu Sisneros, Robert Peterka, Tom Antoniu, Gabriel Semeraro, Dave ENS Cachan Brittany IRISA Rennes France University of Illinois at Urbana-Champaign United States Argonne National Laboratory United States INRIA Rennes Bretagne-Atlantique France

ISBN: (纸本)9781479916597

Reducing the amount of data stored by simulations will be of utmost importance for the next generation of large-scale computing. Accordingly, there is active research to shift analysis and visualization tasks to run in situ, that is, closer to the simulation via the sharing of some resources. This is beneficial as it can avoid the necessity of storing large amounts of data for post-processing. In this paper, we focus on the specific case of in situ visualization where analysis codes are collocated with the simulation's code and run on the same resources. It is important for an in situ technique to require minimum modifications to existing codes, be adaptable, and have a low impact on both run times and resource usage. We accomplish this through the Damaris/Viz framework, which provides in situ visualization support to the Damaris I/O middleware. The use of Damaris as a bridge to existing visualization packages allows us to (1) reduce code moditication to a minimum for existing simulations, (2) gather capabilities of several visualization tools to offer a unified data management interface, (3) use dedicated cores to hide the run time impact of in situ visualization and (4) efficiently use memory through a shared-memory-based communication model. Experiments are conducted on Blue Waters and Grid'5000 to visualize the CM1 atmospheric simulation and the Nek5000 CFD solver. © 2013 ieee.

关键词： Middleware

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Application-specific compression of large MD data preserving physical characteristics

Application-specific compression of large MD data preserving...

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2013 3rd ieee symposium on large-scale data analysis and visualization, ldav 2013

作者： Gralka, Patrick Grottel, Sebastian Reina, Guido Ertl, Thomas

ISBN: (纸本)9781479916597

Application areas like physics or thermodynamics often require simulations of very large data sets, up to the order of 1012 particles or even larger, to obtain results relevant for realistic industrial processes. Persisting such data is too costly, prohibiting interactive visual analysis in a classical post-processing fashion. Thus, analysis is restricted to statistical aggregation or visual in-situ exploration, both requiring an inkling of the results beforehand. We alleviate this issue by applying an application-optimized lossy compression. Reducing the size while at the same time preserving relevant physical characteristics of the data allows for accessibility on workstations and practical long-term storage. The compression is achieved by generating a density volume that is processed using wavelet decomposition, quantization and run-length encoding. Our reconstruction of particle data ensures the restoration of physically relevant properties. It employs a model based on stochastic distributions complemented by further adjustments. We evaluate the precision of the reconstruction for several data sets and a wide range of compression variants to show the effectiveness and user-adjustable trade-offs of the presented method. © 2013 ieee.

关键词： Wavelet decomposition

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