Výsledky vyhľadávania - "2011 IEEE Symposium on Large Data Analysis and Visualization"

The ParaView Coprocessing Library: A scalable, general purpose in situ visualization library Autor Fabian, N., Moreland, K., Thompson, D., Bauer, A. C., Marion, P., Gevecik, B., Rasquin, M., Jansen, K. E.

“…As high performance computing approaches exascale, CPU capability far outpaces disk write speed, and in situ visualization becomes an essential part of an…”
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Analysis of large-scale scalar data using hixels Autor Thompson, D., Levine, J. A., Bennett, J. C., Bremer, Peer-Timo, Gyulassy, A., Pascucci, V., Pebay, P. P.

“…One of the greatest challenges for today's visualization and analysis communities is the massive amounts of data generated from state of the art simulations…”
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Toward simulation-time data analysis and I/O acceleration on leadership-class systems Autor Vishwanath, V., Hereld, M., Papka, M. E.

“…The performance mismatch between computing and I/O components of current-generation HPC systems has made I/O the critical bottleneck for scientific…”
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Revisiting wavelet compression for large-scale climate data using JPEG 2000 and ensuring data precision Autor Woodring, J., Mniszewski, S., Brislawn, C., DeMarle, D., Ahrens, J.

“…We revisit wavelet compression by using a standards-based method to reduce large-scale data sizes for production scientific computing. Many of the bottlenecks…”
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Scalable parallel building blocks for custom data analysis Autor Peterka, T., Ross, R., Gyulassy, A., Pascucci, V., Kendall, W., Han-Wei Shen, Teng-Yok Lee, Chaudhuri, A.

“…We present a set of building blocks that provide scalable data movement capability to computational scientists and visualization researchers for writing their…”
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Parallel in situ indexing for data-intensive computing Autor Jinoh Kim, Abbasi, H., Chacon, L., Docan, C., Klasky, S., Qing Liu, Podhorszki, N., Shoshani, A., Kesheng Wu

“…As computing power increases exponentially, vast amount of data is created by many scientific research activities. However, the bandwidth for storing the data…”
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Dax Toolkit: A proposed framework for data analysis and visualization at Extreme Scale Autor Moreland, K., Ayachit, U., Geveci, B., Kwan-Liu Ma

“…Experts agree that the exascale machine will comprise processors that contain many cores, which in turn will necessitate a much higher degree of concurrency…”
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Parallel visualization on large clusters using MapReduce Autor Vo, H. T., Bronson, J., Summa, B., Comba, J. L. D., Freire, J., Howe, B., Pascucci, V., Silva, C. T.

“…Large-scale visualization systems are typically designed to efficiently "push" datasets through the graphics hardware. However, exploratory visualization…”
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Incremental, approximate database queries and uncertainty for exploratory visualization Autor Fisher, D.

“…Exploratory data visualization calls for iterative analyses, but very large databases are often far too slow to allow interactive exploration. Incremental,…”
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Evaluating the benefits of an extended memory hierarchy for parallel streamline algorithms Autor Camp, D., Childs, H., Chourasia, A., Garth, C., Joy, K. I.

“…The increasing cost of achieving sufficient I/O bandwidth for high end supercomputers is leading to architectural evolutions in the I/O subsystem space…”
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Parallel clustering for visualizing large scientific line data Autor Jishang Wei, Hongfeng Yu, Chen, J. H., Kwan-Liu Ma

“…Scientists often need to extract, visualize and analyze lines from vast amounts of data to understand dynamic structures and interactions. The effectiveness of…”
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Visualizing multiscale, multiphysics simulation data: Brain blood flow Autor Insley, J. A., Grinberg, L., Papka, M. E.

“…Accurately predicting many physical and biological systems requires modeling interactions of macroscopic and microscopic events. This results in large and…”
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CERA-TVR: A framework for interactive high-quality teravoxel volume visualization on standard PCs Autor Engel, K.

“…We present a volume visualization framework that allows high-quality interactive rendering of teravoxel scale volume data sets on standard PCs. It is based on…”
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Atypical behavior identification in large-scale network traffic Autor Best, D. M., Hafen, R. P., Olsen, B. K., Pike, W. A.

“…Cyber analysts are faced with the daunting challenge of identifying exploits and threats within potentially billions of daily records of network traffic…”
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A system for scalable visualization of geographic archival records Autor Heard, J. R., Marciano, R. J.

“…We present a system that visualizes large collections of archival geographic records. This system is comprised of a data grid containing a 60TB test collection…”
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Data-intensive analysis for scientific experiments at the Large Scale Data Facility Autor Garcia, A. O., Bourov, S., Hammad, A., Hartmann, V., Jejkal, T., Otte, J. C., Pfeiffer, S., Schenker, T., Schmidt, C., Neuberger, P., Stotzka, R., van Wezel, J., Neumair, B., Streit, A.

“…The Large Scale Data Facility (LSDF) was conceived and launched at the Karlsruhe Institute of Technology (KIT) end of 2009 to address the growing need for…”
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Histogram spectra for multivariate time-varying volume LOD selection Autor Martin, S., Han-Wei Shen

“…Level of detail techniques are widely applied to minimize sampling error subject to working set size constraints. Typical large data sets being produced today…”
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Distributed terascale volume visualization using distributed shared virtual memory Autor Beyer, J., Hadwiger, M., Schneider, J., Won-Ki Jeong, Pfister, H.

“…Each cluster node is running its own pipeline for ray-casting, virtual vol- ume and memory management, and paging. Ray-casting is per- formed on a huge virtual…”
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Activity Detection for scientific visualization Autor Ozer, S., Silver, D., Bemis, K., Martin, P., Takle, J.

“…Understanding the science behind ultra-scale simulations requires extracting meaning from data sets of hundreds of terabytes or more. At extreme scales, the…”
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Exploring large data over wide area networks Autor Hereld, M., Insley, J. A., Olson, E. C., Papka, M. E., Vishwanath, V., Norman, M. L., Wagner, R.

“…Simulations running on the top supercomputers are routinely producing multi-terabyte data sets. Enabling scientists, at their home institutions, to analyze,…”
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