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检索条件"任意字段=IEEE Symposium on Parallel and Large-Data Visualization and Graphics"

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Evaluating the benefits of an extended memory hierarchy for parallel streamline algorithms

Evaluating the benefits of an extended memory hierarchy for ...

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1st ieee symposium on large-Scale data Analysis and visualization 2011, LDAV 2011

作者： Camp, David Childs, Hank Chourasia, Amit Garth, Christoph Joy, Kenneth I. Lawrence Berkeley National Laboratory Department of Computer Science University of California Davis CA United States San Diego Supercomputer Center University of California San Diego CA United States Department of Computer Science University of California Davis CA United States

ISBN: (纸本)9781467301541

The increasing cost of achieving sufficient I/O bandwidth for high end supercomputers is leading to architectural evolutions in the I/O subsystem space. Currently popular designs create a staging area on each compute node for data output via solid state drives (SSDs), local hard drives, or both. In this paper, we investigate whether these extensions to the memory hierarchy, primarily intended for computer simulations that produce data, can also benefit visualization and analysis programs that consume data. Some algorithms, such as those that read the data only once and store the data in primary memory, can not draw obvious benefit from the presence of a deeper memory hierarchy. However, algorithms that read data repeatedly from disk are excellent candidates, since the repeated reads can be accelerated by caching the first read of a block on the new resources (i.e. SSDs or hard drives). We study such an algorithm, streamline computation, and quantify the benefits it can derive. © 2011 ieee.

关键词： Supercomputers

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Conformal visualization for Partially-Immersive Platforms

Conformal Visualization for Partially-Immersive Platforms

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ieee Virtual Reality Conference (VR)

作者： Petkov, Kaloian Papadopoulos, Charilaos Zhang, Min Kaufman, Arie E. Gu, Xianfeng SUNY Stony Brook Dept Comp Sci Stony Brook NY 11794 USA

ISBN: (纸本)9781457700361

Current VR systems such as the CAVE provide an effective platform for the immersive exploration of large 3D data. A major limitation is that in most cases at least one display surface, such as a ceiling or a back wall, is missing due to space, access or cost constraints. This partially-immersive visualization results in a substantial loss of visual information that may be acceptable for some applications;however, it becomes a major obstacle for critical tasks that need to utilize the users' entire field of vision. We have developed a conformal rendering pipeline for the visualization of datasets on partially-immersive platforms. The angle-preserving conformal mapping approach is used to render the 360. view directly onto arbitrary display configurations. It has the desirable property of preserving shapes locally, which is important for identifying shape-based features in the data. Our conformal visualization technique is applicable to rasterization, volume rendering and real-time raytracing, and in contrast to image-based retargeting approaches, it constructs accurate, artifact-free stereoscopic images. We demonstrate our conformal visualization pipeline in the 5-sided CAVE for Immersive Virtual Colonoscopy, as well as architectural and abstract data exploration. Our user study shows that on the visual polyp detection task, conformal visualization leads to improved sensitivity at comparable examination times against the traditional rendering approach.

关键词： I.3.3 [Computer graphics]: Picture/Image GenerationDisplay Algorithms I.3.7 [Computer graphics]: Three-Dimensional graphics and RealismVirtual Reality

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HiTSEE: A visualization tool for hit selection and analysis in high-throughput screening experiments

HiTSEE: A visualization tool for hit selection and analysis ...

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1st ieee symposium on Biological data visualization, BioVis 2011

作者： Bertini, Enrico Strobelt, Hendrik Braun, Joachim Deussen, Oliver Groth, Ulrich Mayer, Thomas U. Merhof, Dorit University of Konstanz Germany

ISBN: (纸本)9781467300025

We present HiTSEE (High-Throughput Screening Exploration Environment) a visualization tool for the analysis of large chemical screens for the analysis of biochemical processes. The tool supports the analysis of structure-activity relationships (SAR analysis) and, through a flexible interaction mechanism, the navigation of large chemical spaces. Our approach based on the projection of one or few molecules of interest and the expansion around their neighborhood allows for the exploration of large chemical libraries without the need to create an all encompassing overview of the whole library. We describe the requirements we collected during our collaboration with biologists and chemists, the design rationale behind the tool, and two case studies. © 2011 ieee.

关键词： Throughput

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The ParaView coprocessing library: A scalable, general purpose in situ visualization library

The ParaView coprocessing library: A scalable, general purpo...

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1st ieee symposium on large-Scale data Analysis and visualization 2011, LDAV 2011

作者： Fabian, Nathan Moreland, Kenneth Thompson, David Bauer, Andrew C. Marion, Pat Gevecik, Berk Rasquin, Michel Jansen, Kenneth E. Sandia National Laboratories United States Kitware Inc. United States University of Colorado Boulder CO United States

ISBN: (纸本)9781467301541

As high performance computing approaches exascale, CPU capability far outpaces disk write speed, and in situ visualization becomes an essential part of an analyst's workflow. In this paper, we describe the ParaView Coprocessing Library, a framework for in situ visualization and analysis coprocessing. We describe how coprocessing algorithms (building on many from VTK) can be linked and executed directly from within a scientific simulation or other applications that need visualization and analysis. We also describe how the ParaView Coprocessing Library can write out partially processed, compressed, or extracted data readable by a traditional visualization application for interactive post-processing. Finally, we will demonstrate the library's scalability in a number of real-world scenarios. © 2011 ieee.

关键词： data visualization

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Visualizing virus population variability from next generation sequencing data

Visualizing virus population variability from next generatio...

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1st ieee symposium on Biological data visualization, BioVis 2011

作者： Correll, Michael Ghosh, Subhadip O'Connor, David Gleicher, Michael University of Wisconsin Madison United States Department of Computer Sciences United States Department of Pathology and Laboratory Medicine United States

ISBN: (纸本)9781467300025

Advances in genomic sequencing techniques allow for larger scale generation and usage of sequence data. While these techniques afford new types of analysis, they also generate new concerns with regards to data quality and data scale. We present a tool designed to assist in the exploration of the genetic variability of the population of viruses at multiple time points and in multiple individuals, a task that necessitates considering large amounts of sequence data and the quality issues inherent in obtaining such data in a practical manner. Our design affords the examination of the amount of variability and mutation at each position in the genome for many populations of viruses. Our design contains novel visualization techniques that support this specific class of analysis while addressing the issues of data aggregation, confidence visualization, and interaction support that arise when making use of large amounts of sequence data with variable uncertainty. These techniques generalize to a wide class of visualization problems where confidence is not known a priori, and aggregation in multiple directions is necessary. © 2011 ieee.

关键词： visualization

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Toward simulation-time data analysis and I/O acceleration on leadership-class systems

Toward simulation-time data analysis and I/O acceleration on...

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1st ieee symposium on large-Scale data Analysis and visualization 2011, LDAV 2011

作者： Vishwanath, Venkatram Hereld, Mark Papka, Michael E. Argonne National Laboratory 9700 South Cass Avenue Argonne IL 60439 United States

ISBN: (纸本)9781467301541

The performance mismatch between computing and I/O components of current-generation HPC systems has made I/O the critical bottleneck for scientific applications. It is therefore critical to make data movement as efficient as possible, and, to facilitate simulation-time data analysis and visualization to reduce the data written to storage. These will be of paramount importance to enabling us to glean novel insights from simulations. We present our work in GLEAN, a flexible framework for data-analysis and I/O acceleration at extreme scale. GLEAN leverages the data semantics of applications, and fully exploits the diverse system topologies and characteristics. We discuss the performance of GLEAN for simulation-time analysis and I/O acceleration with simulations at scale on leadership class systems. © 2011 ieee.

关键词： data visualization

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Atypical behavior identification in large-scale network traffic

Atypical behavior identification in large-scale network traf...

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1st ieee symposium on large-Scale data Analysis and visualization 2011, LDAV 2011

作者： Best, Daniel M. Hafen, Ryan P. Olsen, Bryan K. Pike, William A. Pacific Northwest National Laboratory United States

ISBN: (纸本)9781467301541

Cyber analysts are faced with the daunting challenge of identifying exploits and threats within potentially billions of daily records of network traffic. Enterprise-wide cyber traffic involves hundreds of millions of distinct IP addresses and results in data sets ranging from terabytes to petabytes of raw data. Creating behavioral models and identifying trends based on those models requires data intensive architectures and techniques that can scale as data volume increases. Analysts need scalable visualization methods that foster interactive exploration of data and enable identification of behavioral anomalies. Developers must carefully consider application design, storage, processing, and display to provide usability and interactivity with large-scale data. We present an application that highlights atypical behavior in enterprise network flow records. This is accomplished by utilizing data intensive architectures to store the data, aggregation techniques to optimize data access, statistical techniques to characterize behavior, and a visual analytic environment to render the behavioral trends, highlight atypical activity, and allow for exploration. © 2011 ieee.

关键词： data visualization

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Interactive visualization of streaming data with Kernel Density Estimation

Interactive visualization of streaming data with Kernel Dens...

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ieee Pacific visualization symposium

作者： Daae Lampe, Ove Hauser, Helwig University of Bergen Norway

ISBN: (纸本)9781612849324

In this paper, we discuss the extension and integration of the statistical concept of Kernel Density Estimation (KDE) in a scatterplot-like visualization for dynamic data at interactive rates. We present a line kernel for representing streaming data, we discuss how the concept of KDE can be adapted to enable a continuous representation of the distribution of a dependent variable of a 2D domain. We propose to automatically adapt the kernel bandwith of KDE to the viewport settings, in an interactive visualization environment that allows zooming and panning. We also present a GPU-based realization of KDE that leads to interactive frame rates, even for comparably large datasets. Finally, we demonstrate the usefulness of our approach in the context of three application scenarios - one studying streaming ship traffic data, another one from the oil & gas domain, where process data from the operation of an oil rig is streaming in to an on-shore operational center, and a third one studying commercial air traffic in the US spanning 1987 to 2008. © 2011 ieee.

关键词： visualization

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parallel in situ indexing for data-intensive computing

Parallel in situ indexing for data-intensive computing

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1st ieee symposium on large-Scale data Analysis and visualization 2011, LDAV 2011

作者： Kim, Jinoh Abbasi, Hasan Chacón, Luis Docan, Ciprian Klasky, Scott Liu, Qing Podhorszki, Norbert Shoshani, Arie Wu, Kesheng Lawrence Berkeley National Lab. United States University of Tennessee Knoxville TX United States Oak Ridge National Lab. United States Rutgers University United States

ISBN: (纸本)9781467301541

As computing power increases exponentially, vast amount of data is created by many scientific research activities. However, the bandwidth for storing the data to disks and reading the data from disks has been improving at a much slower pace. These two trends produce an ever-widening data access gap. Our work brings together two distinct technologies to address this data access issue: indexing and in situ processing. From decades of database research literature, we know that indexing is an effective way to address the data access issue, particularly for accessing relatively small fraction of data records. As data sets increase in sizes, more and more analysts need to use selective data access, which makes indexing an even more important for improving data access. The challenge is that most implementations of indexing technology are embedded in large database management systems (DBMS), but most scientific datasets are not managed by any DBMS. In this work, we choose to include indexes with the scientific data instead of requiring the data to be loaded into a *** use compressed bitmap indexes from the FastBit software which are known to be highly effective for query-intensive workloads common to scientific data analysis. To use the indexes, we need to build them first. The index building procedure needs to access the whole data set and may also require a significant amount of compute time. In this work, we adapt the in situ processing technology to generate the indexes, thus removing the need of reading data from disks and to build indexes in parallel. The in situ data processing system used is ADIOS, a middleware for high-performance I/O. Our experimental results show that the indexes can improve the data access time up to 200 times depending on the fraction of data selected, and using in situ data processing system can effectively reduce the time needed to create the indexes, up to 10 times with our in situ technique when using identical parallel settings. © 2011

关键词： Middleware

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EGPGV 2011 - 11th Eurographics symposium on parallel graphics and visualization

EGPGV 2011 - 11th Eurographics Symposium on Parallel Graphic...

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11th Eurographics symposium on parallel graphics and visualization, EGPGV 2011

ISBN: (纸本)9783905674323

The proceedings contain 14 papers. The topics discussed include: optimal multi-image processing streaming framework on parallel heterogeneous systems;parallel gradient domain processing of massive images;distributed OpenGL rendering in network bandwidth constrained environments;revisiting parallel rendering for shared memory machines;cross-segment load balancing in parallel rendering;load balancing utilizing data redundancy in distributed volume rendering;real-time ray tracer for visualizing massive models on a cluster;interactive particle tracing in time-varying tetrahedral grids;efficient I/O for parallel visualization;parallel computational steering and analysis for HPC applications using a ParaView interface and the HDF5 DSM virtual file driver;parallel in situ coupling of simulation with a fully featured visualization system;and a preview and exploratory technique for large-scale scientific simulations.

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