Computing in Science & Engineering

Issue 6 • Nov.-Dec. 2015

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Displaying Results 1 - 23 of 23
  • Front Cover

    Publication Year: 2015, Page(s): c1
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  • Rock Stars of Cybersecurity

    Publication Year: 2015, Page(s): c2
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  • Masthead

    Publication Year: 2015, Page(s): 1
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  • Table of Contents

    Publication Year: 2015, Page(s):2 - 3
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  • Cloudy with a Chance of Sunshine, or the Future of Magazine Publishing

    Publication Year: 2015, Page(s):4 - 5
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  • Computing and Climate

    Publication Year: 2015, Page(s):6 - 8
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  • Climate Computing: The State of Play

    Publication Year: 2015, Page(s):9 - 13
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (486 KB) | HTML iconHTML

    Climate models represent a large variety of processes on different time and space scales and canonical example of multiphysics, multiscale modeling. In addition, the system is physically characterized by sensitive dependence on initial conditions and natural stochastic variability, with very long integrations needed to extract signals of climate change. Weak scaling, I/O, and memory-bound multiphy... View full abstract»

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  • A Guide to Earth Science Data: Summary and Research Challenges

    Publication Year: 2015, Page(s):14 - 18
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (563 KB) | HTML iconHTML

    Recent growth in the scale and variety of Earth science data has provided unprecedented opportunities to big data analytics research for understanding the Earth's physical processes. An upsurge of Earth science datasets in the past few decades are being continually collected using various modes of acquisition, at different scales of observation, and in diverse data types and formats. Earth science... View full abstract»

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  • Scalable Multivariate Time-Series Models for Climate Informatics

    Publication Year: 2015, Page(s):19 - 26
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2032 KB) | HTML iconHTML

    The increasing volume of climate data has created the need for scientists to develop scalable data analysis tools beyond traditional techniques. Climate data not only have a massive scale but also high dimension and complex dependency structures, making the analysis task extremely challenging. Climate informatics leverages advanced algorithmic tools from data science to solve problems in climate s... View full abstract»

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  • Identifying Physical Interactions from Climate Data: Challenges and Opportunities

    Publication Year: 2015, Page(s):27 - 34
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2704 KB) | HTML iconHTML

    Recent research has shown the potential of using structure learning from probabilistic graphical models to identify and visualize interactions in the Earth's climate system by training them on observed climate data. The resulting models indicate pathways of physical interactions occurring within a subsystem of the climate (such as the atmosphere) or between different subsystems (such as from ocean... View full abstract»

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  • A Multitask Learning View on the Earth System Model Ensemble

    Publication Year: 2015, Page(s):35 - 42
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3400 KB) | HTML iconHTML

    Earth system models (ESMs) are based on physical principles that are intended to emulate climate behavior. They're the primary mechanisms for obtaining projections of future conditions under different climate change scenarios. Because ESMs rely on the distinct modeling of certain physical processes and initial conditions, different ESMs can produce different responses for the same external forcing... View full abstract»

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  • Can Topic Modeling Shed Light on Climate Extremes?

    Publication Year: 2015, Page(s):43 - 52
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2987 KB) | HTML iconHTML

    Understanding changes in climate extremes is an urgent challenge. Topic modeling techniques from natural language processing can help scientists learn climate patterns from data. The authors' work extracts global climate patterns from multivariate climate data, modeling relations between variables via latent topics and discovering the probability of each climate topic appearing at different geogra... View full abstract»

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  • Climate Adaptation Informatics: Water Stress on Power Production

    Publication Year: 2015, Page(s):53 - 60
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2667 KB) | HTML iconHTML

    Resilience to nonstationarity and deep uncertainty is a prerequisite to water security. Stakeholder planning horizons typically extend to about 30 years in water quantity or quality management, flood or drought hazard resilience, or the water-energy-food-ecosystems nexus. Projections of stressors, such as population, land use, stability assumptions of technologies, infrastructures, and organizatio... View full abstract»

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  • The Evolution of Global Scale Filesystems for Scientific Software Distribution

    Publication Year: 2015, Page(s):61 - 71
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (321 KB) | HTML iconHTML

    Delivering complex software across a worldwide distributed system is a major challenge in high-throughput scientific computing. The problem arises at different scales for many scientific communities that use grids, clouds, and distributed clusters to satisfy their computing needs. For high-energy physics (HEP) collaborations dealing with large amounts of data that rely on hundreds of thousands of ... View full abstract»

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  • Designing Biological Simulation Models Using Formalism-Based Functional and Spatial Decompositions

    Publication Year: 2015, Page(s):72 - 82
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2505 KB) | HTML iconHTML

    One of the most daunting challenges confronting computational biologists is a problem that simulation developers in all disciplines face: the design of simulation code that can be easily understood and modified despite the complexity of the systems being modeled. To meet this challenge, the authors apply the discrete event system specification (DEVS), a general modeling formalism invented for the ... View full abstract»

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  • Exploiting Very-Wide Vector Processing for Scientific Applications

    Publication Year: 2015, Page(s):83 - 87
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1895 KB) | HTML iconHTML

    Exploiting the recently introduced very-wide vector units of the Xeon Phi coprocessor can potentially increase the scalability for scientific applications. Using lattice QCD compute kernels, the authors find that the performance achieved using the Xeon Phi coprocessors wide vector units is similar to GPGPU performance after appropriate code refactoring, requiring moderate programming effort. View full abstract»

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  • Our Dynamic Future

    Publication Year: 2015, Page(s):88 - 90
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1818 KB) | HTML iconHTML

    For decades, programmers have leveraged a very stable abstract machine for large-scale parallel computation: processors that could run equally sized chunks of work in equal time were connected via a fast interconnect. This very simple abstraction has served us quite well, allowing portable and scalable codes to be run across a wide range of platforms. However, as the semiconductor industry has pus... View full abstract»

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  • Is This for Real? Fast Graphicality Testing

    Publication Year: 2015, Page(s):91 - 95
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1603 KB) | HTML iconHTML

    One of the major advances in modeling networks is the realization that many of them (social, Internet, power grid, and so on) have predictable degree sequences-that is, the expected number of connections from a given node comes from some well-understood distribution. Models of these networks usually begin with random graphs whose degrees have the desired degree distribution. One task that repeated... View full abstract»

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  • A Flight through the Universe

    Publication Year: 2015, Page(s):96 - 102
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    The authors describe the creation of a tridimensional fly-through animation across the largest map of galaxies to date. This project represented a challenge: creating a scientifically accurate representation of the galaxy distribution that was aesthetically pleasing. The animation shows almost half a million galaxies as the viewer travels through the vast intergalactic regions, giving a glimpse of... View full abstract»

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  • Technical Debt in Computational Science

    Publication Year: 2015, Page(s):103 - 107
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1155 KB) | HTML iconHTML

    Technical debt is a useful metaphor for understanding the long-term impact of technical choices. The analysis of technical debt has found its place in the software industry, with results that are applicable to scientific software as well. But technical debt is also a useful concept to look at how we use computers in doing scientific research. View full abstract»

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  • Astronomical Images before the Internet

    Publication Year: 2015, Page(s): 108
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  • Back Covers 
  • Call for Standards Award Nominations

    Publication Year: 2015, Page(s): c3
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  • Call for nominees

    Publication Year: 2015, Page(s): c4
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Aims & Scope

CS&E magazine emphasizes articles that help define the field as the interface among the applications (in science and engineering), algorithms (numerical and symbolic), system software, and computer architecture.

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Meet Our Editors

Editor-in-Chief
George K. Thiruvathukal
Loyola University