DOE's SciDAC Visualization and Analytics Center for EnablingTechnologies -- Strategy for Petascale Visual Data Analysis Success

DOE's SciDAC Visualization and Analytics Center for EnablingTechnologies -- Strategy for Petascale Visual Data Analysis Success

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Published: 2007

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The focus of this article is on how one group of researchersthe DOE SciDAC Visualization and Analytics Center for EnablingTechnologies (VACET) is tackling the daunting task of enabling knowledgediscovery through visualization and analytics on some of the world slargest and most complex datasets and on some of the world's largestcomputational platforms. As a Center for Enabling Technology, VACET smission is the creation of usable, production-quality visualization andknowledge discovery software infrastructure that runs on large, parallelcomputer systems at DOE's Open Computing facilities and that providessolutions to challenging visual data exploration and knowledge discoveryneeds of modern science, particularly the DOE sciencecommunity.


SciDAC Visualization and Analytics Center for EnablingTechnologies

SciDAC Visualization and Analytics Center for EnablingTechnologies

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Publisher:

Published: 2007

Total Pages:

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The Visualization and Analytics Center for EnablingTechnologies (VACET) focuses on leveraging scientific visualization andanalytics software technology as an enabling technology for increasingscientific productivity and insight. Advances in computational technologyhave resulted in an 'information big bang, ' which in turn has created asignificant data understanding challenge. This challenge is widelyacknowledged to be one of the primary bottlenecks in contemporaryscience. The vision of VACET is to adapt, extend, create when necessary, and deploy visual data analysis solutions that are responsive to theneeds of DOE'scomputational and experimental scientists. Our center isengineered to be directly responsive to those needs and to deliversolutions for use in DOE's large open computing facilities. The researchand development directly target data understanding problems provided byour scientific application stakeholders. VACET draws from a diverse setof visualization technology ranging from production quality applicationsand application frameworks to state-of-the-art algorithms forvisualization, analysis, analytics, data manipulation, and datamanagement.


SciDAC Visualization and Analytics Center for Enabling Technologies

SciDAC Visualization and Analytics Center for Enabling Technologies

Author:

Publisher:

Published: 2014

Total Pages: 11

ISBN-13:

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This project focuses on leveraging scientific visualization and analytics software technology as an enabling technology for increasing scientific productivity and insight. Advances in computational technology have resulted in an "information big bang," which in turn has created a significant data understanding challenge. This challenge is widely acknowledged to be one of the primary bottlenecks in contemporary science. The vision for our Center is to respond directly to that challenge by adapting, extending, creating when necessary and deploying visualization and data understanding technologies for our science stakeholders. Using an organizational model as a Visualization and Analytics Center for Enabling Technologies (VACET), we are well positioned to be responsive to the needs of a diverse set of scientific stakeholders in a coordinated fashion using a range of visualization, mathematics, statistics, computer and computational science and data management technologies.


VACET

VACET

Author: Mark Duchaineau

Publisher:

Published: 2006

Total Pages:

ISBN-13:

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This paper accompanies a poster that is being presented atthe SciDAC 2006 meeting in Denver, CO. This project focuses on leveragingscientific visualization and analytics software technology as an enablingtechnology for increasing scientific productivity and insight. Advancesincomputational technology have resultedin an "information big bang, "which in turn has createda significant data understanding challenge. Thischallenge is widely acknowledged to be one of the primary bottlenecks incontemporary science. The vision for our Center is to respond directly tothat challenge by adapting, extending, creating when necessary anddeploying visualization and data understanding technologies for ourscience stakeholders. Using an organizational model as a Visualizationand Analytics Center for Enabling Technologies (VACET), we are wellpositioned to be responsive to the needs of a diverse set of scientificstakeholders in a coordinated fashion using a range of visualization, mathematics, statistics, computer and computational science and datamanagement technologies.


Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration

Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration

Author: Torsten Möller

Publisher: Springer Science & Business Media

Published: 2009-06-12

Total Pages: 348

ISBN-13: 3540499261

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The goal of visualization is the accurate, interactive, and intuitive presentation of data. Complex numerical simulations, high-resolution imaging devices and incre- ingly common environment-embedded sensors are the primary generators of m- sive data sets. Being able to derive scienti?c insight from data increasingly depends on having mathematical and perceptual models to provide the necessary foundation for effective data analysis and comprehension. The peer-reviewed state-of-the-art research papers included in this book focus on continuous data models, such as is common in medical imaging or computational modeling. From the viewpoint of a visualization scientist, we typically collaborate with an application scientist or engineer who needs to visually explore or study an object which is given by a set of sample points, which originally may or may not have been connected by a mesh. At some point, one generally employs low-order piecewise polynomial approximationsof an object, using one or several dependent functions. In order to have an understanding of a higher-dimensional geometrical “object” or function, ef?cient algorithms supporting real-time analysis and manipulation (- tation, zooming) are needed. Often, the data represents 3D or even time-varying 3D phenomena (such as medical data), and the access to different layers (slices) and structures (the underlying topology) comprising such data is needed.


High Performance Computing

High Performance Computing

Author: Julian M. Kunkel

Publisher: Springer

Published: 2016-06-15

Total Pages: 506

ISBN-13: 9783319413204

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This book constitutes the refereed proceedings of the 31st International Conference, ISC High Performance 2016 [formerly known as the International Supercomputing Conference] held in Frankfurt, Germany, in June 2016. The 25 revised full papers presented in this book were carefully reviewed and selected from 60 submissions. The papers cover the following topics: Autotuning and Thread Mapping; Data Locality and Decomposition; Scalable Applications; Machine Learning; Datacenters andCloud; Communication Runtime; Intel Xeon Phi; Manycore Architectures; Extreme-scale Computations; and Resilience.


Hadoop: The Definitive Guide

Hadoop: The Definitive Guide

Author: Tom White

Publisher: "O'Reilly Media, Inc."

Published: 2012-05-10

Total Pages: 687

ISBN-13: 1449338771

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Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN). Store large datasets with the Hadoop Distributed File System (HDFS) Run distributed computations with MapReduce Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud Load data from relational databases into HDFS, using Sqoop Perform large-scale data processing with the Pig query language Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems


Visualization and Processing of Tensor Fields

Visualization and Processing of Tensor Fields

Author: David H. Laidlaw

Publisher: Springer Science & Business Media

Published: 2009-03-30

Total Pages: 379

ISBN-13: 3540883789

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This book provides researchers an inspirational look at how to process and visualize complicated 2D and 3D images known as tensor fields. With numerous color figures, it details both the underlying mathematics and the applications of tensor fields.


Visualization Handbook

Visualization Handbook

Author: Charles D. Hansen

Publisher: Elsevier

Published: 2011-08-30

Total Pages: 1061

ISBN-13: 0080481647

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The Visualization Handbook provides an overview of the field of visualization by presenting the basic concepts, providing a snapshot of current visualization software systems, and examining research topics that are advancing the field. This text is intended for a broad audience, including not only the visualization expert seeking advanced methods to solve a particular problem, but also the novice looking for general background information on visualization topics. The largest collection of state-of-the-art visualization research yet gathered in a single volume, this book includes articles by a “who’s who of international scientific visualization researchers covering every aspect of the discipline, including:· Virtual environments for visualization· Basic visualization algorithms· Large-scale data visualization· Scalar data isosurface methods· Visualization software and frameworks· Scalar data volume rendering· Perceptual issues in visualization· Various application topics, including information visualization. * Edited by two of the best known people in the world on the subject; chapter authors are authoritative experts in their own fields;* Covers a wide range of topics, in 47 chapters, representing the state-of-the-art of scientific visualization.


High Performance Visualization

High Performance Visualization

Author: E. Wes Bethel

Publisher: CRC Press

Published: 2012-10-25

Total Pages: 520

ISBN-13: 1439875731

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Visualization and analysis tools, techniques, and algorithms have undergone a rapid evolution in recent decades to accommodate explosive growth in data size and complexity and to exploit emerging multi- and many-core computational platforms. High Performance Visualization: Enabling Extreme-Scale Scientific Insight focuses on the subset of scientifi