Workflows for e-Science

Workflows for e-Science

Author: Ian J. Taylor

Publisher: Springer Science & Business Media

Published: 2007-12-31

Total Pages: 532

ISBN-13: 184628757X

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This is a timely book presenting an overview of the current state-of-the-art within established projects, presenting many different aspects of workflow from users to tool builders. It provides an overview of active research, from a number of different perspectives. It includes theoretical aspects of workflow and deals with workflow for e-Science as opposed to e-Commerce. The topics covered will be of interest to a wide range of practitioners.


Frontiers in High Energy Density Physics

Frontiers in High Energy Density Physics

Author: National Research Council

Publisher: National Academies Press

Published: 2003-05-11

Total Pages: 177

ISBN-13: 030908637X

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Recent scientific and technical advances have made it possible to create matter in the laboratory under conditions relevant to astrophysical systems such as supernovae and black holes. These advances will also benefit inertial confinement fusion research and the nation's nuclear weapon's program. The report describes the major research facilities on which such high energy density conditions can be achieved and lists a number of key scientific questions about high energy density physics that can be addressed by this research. Several recommendations are presented that would facilitate the development of a comprehensive strategy for realizing these research opportunities.


Grid Resource Management

Grid Resource Management

Author: Jarek Nabrzyski

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 580

ISBN-13: 1461505097

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Grid Resource Management: State of the Art and Future Trends presents an overview of the state of the field and describes both the real experiences and the current research available today. Grid computing is a rapidly developing and changing field, involving the shared and coordinated use of dynamic, multi-institutional resources. Grid resource management is the process of identifying requirements, matching resources to applications, allocating those resources, and scheduling and monitoring Grid resources over time in order to run Grid applications as efficiently as possible. While Grids have become almost commonplace, the use of good Grid resource management tools is far from ubiquitous because of the many open issues of the field, including the multiple layers of schedulers, the lack of control over resources, the fact that resources are shared, and that users and administrators have conflicting performance goals.


Plasma Science

Plasma Science

Author: National Academies of Sciences Engineering and Medicine

Publisher:

Published: 2021-02-28

Total Pages: 291

ISBN-13: 9780309677608

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Plasma Science and Engineering transforms fundamental scientific research into powerful societal applications, from materials processing and healthcare to forecasting space weather. Plasma Science: Enabling Technology, Sustainability, Security and Exploration discusses the importance of plasma research, identifies important grand challenges for the next decade, and makes recommendations on funding and workforce. This publication will help federal agencies, policymakers, and academic leadership understand the importance of plasma research and make informed decisions about plasma science funding, workforce, and research directions.


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.


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.


Topology-based Methods in Visualization

Topology-based Methods in Visualization

Author: Helwig Hauser

Publisher: Springer Science & Business Media

Published: 2007-06-25

Total Pages: 246

ISBN-13:

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This book presents 13 peer-reviewed papers as written results from the 2005 workshop "Topology-Based Methods in Visualization" that was initiated to enable additional stimulation in this field. It contains a survey of the state-of-the-art, as well original work by leading experts that has not been published before, spanning both theory and applications. It captures key concepts and novel ideas and serves as an overview of current trends in its subject.


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