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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"

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VisNEST - Interactive analysis of neural activity data

VisNEST - Interactive analysis of neural activity data

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3rd ieee symposium on Biological data visualization, BioVis 2013

作者： Nowke, Christian Schmidt, Maximilian Van Albada, Sacha J. Eppler, Jochen M. Bakker, Rembrandt Diesrnann, Markus Hentschel, Bernd Kuhlen, Torsten Virtual Reality Group RWTH Aachen University JARA - High Performance Computing Germany Jülich Research Center JARA - Translational Brain Medicine Germany

ISBN: (纸本)9781479916580

The aim of computational neuroscience is to gain insight into the dynamics and functionality of the nervous system by means of modeling and simulation. Current research leverages the power of High Performance Computing facilities to enable multi-scale simulations capturing both low-level neural activity and large-scalce interactions between brain regions. In this paper, we describe an interactive analysis tool that enables neuroscientists to explore data from such simulations. One of the driving challenges behind this work is the integration of macroscopic data at the level of brain regions with microscopic simulation results, such as the activity of individual neurons. While researchers validate their findings mainly by visualizing these data in a non-interactive fashion, state-of-the-art visu-alizations, tailored to the scientific question yet sufficiently general to accommodate different types of models, enable such analyses to be performed more efficiently. This work describes several visualization designs, conceived in close collaboration with domain experts, for the analysis of network models. We primarily focus on the exploration of neural activity data, inspecting connectivity of brain regions and populations, and visualizing activity flux across regions. We demonstrate the effectiveness of our approach in a case study conducted with domain experts. © 2013 ieee.

关键词： visualization

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Interactive rendering and efficient querying for large multivariate seismic volumes on consumer level PCs

Interactive rendering and efficient querying for large multi...

引用

ieee symposium on large data analysis and visualization (ldav)

作者： Liang Zhou Charles Hansen SCI Institute and the School of Computing University of Utah

ISBN: (纸本)9781479924363

We present a volume visualization method that allows interactive rendering and efficient querying of large multivariate seismic volume data on consumer level PCs. The volume rendering pipeline utilizes a virtual memory structure that supports out-of-core multivariate multi-resolution data and a GPU-based ray caster that allows interactive multivariate transfer function design. A Gaussian mixture model representation is precomputed and nearly interactive querying is achieved by testing the Gaussian functions against user defined transfer functions on the GPU in the runtime. Finally, the method has been tested on a multivariate 3D seismic dataset which is larger than the size of the main memory of the testing machine.

关键词： data visualization Transfer functions Graphics processing units Runtime Educational institutions Rendering (computer graphics) Three-dimensional displays

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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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ieee symposium on large data analysis and visualization (ldav)

作者： Omar ElTayeby Dwayne John Pragnesh Patel Scott Simmerman Clark Atlanta University National Institute for Computational Sciences

ISBN: (纸本)9781479924363

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).

关键词： data visualization Libraries Monitoring Correlation Rendering (computer graphics) Educational institutions Indexes

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

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

引用

ieee symposium on large data analysis and visualization (ldav)

作者： Thomas Fogal Alexander Schiewe Jens Krüger HPC Group Duisburg-Essen SCI Intel VCI

ISBN: (纸本)9781479924363

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(N 3 ) 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.

关键词： Graphics processing units Image resolution Abstracts Hardware Rendering (computer graphics) Benchmark testing

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A provably-robust sampling method for generating colormaps of large data

A provably-robust sampling method for generating colormaps o...

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ieee symposium on large data analysis and visualization (ldav)

作者： David Thompson Janine Bennett C. Seshadhri Ali Pinar Kitware Inc Sandia National Laboratories Livermore CA

ISBN: (纸本)9781479924363

First impressions from initial renderings of data are crucial for directing further exploration and analysis. In most visualization systems, default colormaps are generated by simply linearly interpolating color in some space based on a value's placement between the minimum and maximum taken on by the dataset. We design a simple sampling-based method for generating colormaps that high-lights important features. We use random sampling to determine the distribution of values observed in the data. The sample size required is independent of the dataset size and only depends on certain accuracy parameters. This leads to a computationally cheap and robust algorithm for colormap generation. Our approach (1) uses perceptual color distance to produce palettes from color curves, (2) allows the user to either emphasize or de-emphasize prominent values in the data, (3) uses quantiles to map distinct colors to values based on their frequency in the dataset, and (4) supports the highlighting of either inter- or intra-mode variations in the data.

关键词： Image color analysis Approximation methods data visualization Approximation algorithms Market research Bismuth Robustness

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End-to-end data movement using MPI-IO over routed terabits infrastructures

End-to-end data movement using MPI-IO over routed terabits i...

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3rd International Workshop on Network-Aware data Management, NDM 2013 - Held in Conjunction with the International Conference for High Performance Computing, Networking, Storage and analysis, SC 2013

作者： Vallée, Geoffroy Atchley, Scott Kim, Youngjae Shipman, Galen Oak Ridge National Laboratory P.O. Box 2008 Oak Ridge TN 37831 United States

ISBN: (纸本)9781450325226

Scientific discovery is nowadays driven by large-scale simulations running on massively parallel high-performance computing (HPC) systems. These applications each generate a large amount of data, which then needs to be post-processed for example for data mining or visualization. Unfortunately, the computing platform used for post processing might be different from the one on which the data is initially generated, introducing the challenge of moving large amount of data between computing platforms. This is especially challenging when these two platforms are geographically separated since the data needs to be moved between computing facilities. This is even more critical when scientists tightly couple their domain specific applications with a post processing application. The paper presents a solution for the data transfer between MPI applications using a dedicated wide area network (WAN) terabit infrastructure. The proposed solution is based on parallel access to data files and the Message Passing Inter-face (MPI) over the Common Communication Infrastructure (CCI) for the data transfer over a routed infrastructure. In the context of this research, the Energy Sciences Network (ESnet) of the U.S. Department of Energy (DOE) is targeted for the transfer of data between DOE national laboratories. Copyright 2013 ACM.

关键词： Message passing

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An interactive method for activity detection visualization

An interactive method for activity detection visualization

引用

ieee symposium on large data analysis and visualization (ldav)

作者： Li Liu Sedat Ozer Karen Bemis Jay Takle Deborah Silver Department of Electrical & Computer Engineering Rutgers University Department of Marine & Coastal Science Rutgers University

ISBN: (纸本)9781479924363

Visualizing each time step in an activity from a scientific dataset can aid in understanding the data and phenomena. In this work, we present a Graphical User Interface (GUI) that allows scientists to first graphically model an activity, then detect any activities that match the model, and finally visualize the detected activities in time varying scientific data sets. As a graphical and state based interactive approach, an activity detection framework is implemented by our GUI as a tool for modelling, hypothesis-testing and searching for interested activities from the phenomena evolution of the data set. We demonstrate here some features of our GUI: a histogram is used to visualize the number of activities detected as a function of time and to allow the user to focus on a moment in time; a table is used to give details about the activities and the features participating in them; and finally the user is given the ability to click on the screen to bring up 3D images of the overall activity sequence, single time steps of an activity, or individual feature in an activity. We present examples from applications to two different data sets.

关键词： data visualization Graphical user interfaces data models Feature extraction Histograms Semantics Load modeling

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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 ...

引用

ieee symposium on large-scale data analysis and visualization

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

ISBN: (纸本)9781479924363

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.

关键词： Exascale Computing Multicore Architectures I/O In Situ visualization Dedicated Cores

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