Xml In Scientific Computing

While the extensible markup language (XML) has received a great deal of attention in web programming and software engineering, far less attention has been paid to XML in mainstream computational science and engineering. Correcting this imbalance, XML in Scientific Computing introduces XML to scientists and engineers in a way that illustrates the similarities and differences with traditional programming languages and suggests new ways of saving and sharing the results of scientific calculations. The author discusses XML in the context of scientific computing, demonstrates how the extensible stylesheet language (XSL) can be used to perform various calculations, and explains how to create and navigate through XML documents using traditional languages such as Fortran, C++, and MATLAB®. A suite of computer programs are available on the author’s website.

The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of XML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

Web technologies are increasingly relevant to scientists working with data, for both accessing data and creating rich dynamic and interactive displays. The XML and JSON data formats are widely used in Web services, regular Web pages and JavaScript code, and visualization formats such as SVG and KML for Google Earth and Google Maps. In addition, scientists use HTTP and other network protocols to scrape data from Web pages, access REST and SOAP Web Services, and interact with NoSQL databases and text search applications. This book provides a practical hands-on introduction to these technologies, including high-level functions the authors have developed for data scientists. It describes strategies and approaches for extracting data from HTML, XML, and JSON formats and how to programmatically access data from the Web. Along with these general skills, the authors illustrate several applications that are relevant to data scientists, such as reading and writing spreadsheet documents both locally and via Google Docs, creating interactive and dynamic visualizations, displaying spatial-temporal displays with Google Earth, and generating code from descriptions of data structures to read and write data. These topics demonstrate the rich possibilities and opportunities to do new things with these modern technologies. The book contains many examples and case-studies that readers can use directly and adapt to their own work. The authors have focused on the integration of these technologies with the R statistical computing environment. However, the ideas and skills presented here are more general, and statisticians who use other computing environments will also find them relevant to their work. Deborah Nolan is Professor of Statistics at University of California, Berkeley. Duncan Temple Lang is Associate Professor of Statistics at University of California, Davis and has been a member of both the S and R development teams.

This book aims to provide a deep look into Italian actions taken in some fields of science and high performance computing (HPC), and the Italian effort to bridge the HPC gap with respect to Europe. The Italian PON ReCaS Project is written for graduate readers and professionals in the field of high performance computing. It presents and discusses innovative and important technological solutions, and describes interesting results in various fields of application. ReCaS stands for "Rete di Calcolo per SuperB e altre applicazioni" and is a computing network infrastructure in Southern Italy devoted to scientific and non-scientific applications within the vision of a common European infrastructure for computing, storage and network. The ReCaS project is part of the 2007–2013 European Union strategy, and was funded by the Italian Ministry of Research and Education (MIUR) for the development and enhancement of a distributed computing infrastructure of the Grid/Cloud type over the four EU 'Convergence' regions in Southern Italy: Campania, Puglia and Sicily and Calabria. The network will be open and accessible to all researchers, public and private, and will be characterized by unprecedented computing power and storage capacity. Posted in the European Grid Infrastructure EGI, ReCaS is also an opportunity to the countries of the Mediterranean area and extends the potential of the current network.

TheseproceedingscontainthepaperspresentedatPARA2002,theSixth- ternationalConferenceonAppliedParallelComputing. PARA2002washeldin Espoo,Finland,June15–18,2002,andhostedbyCSC,theFinnishinformation technologycenterforscience. Thegeneralthemeoftheconferencewasadvanced scienti?ccomputing. Theconferencedemonstratedtheabilityofadvancedscienti?ccomputingto solvereal-worldproblems,andhighlightedmethods,instruments,andtrendsin futurescienti?ccomputing. Theconferencebeganwithaone-daytutorialsession onGridprogramming. Theconferencefocusedonanapplication-oriented,multi-disciplinary,and multi-scaleapproach. Awidevarietyofscienti?ccomputingapplicationswere introduced,fromsemiconductorprocessingandbehaviorofthehumanbodyto oceanicandatmosphericphenomena. Scienti?ccomputingcoupledwithmulti-disciplinaryandmulti-scaleexp- tisewillplayasigni?cantroleinsolvingchallengingproblemsinscience.

The 7th International Conference on Large-Scale Scienti?c Computations (LSSC 2009) was held in Sozopol, Bulgaria, June 4–8, 2009. The conference was organized and sponsored by the Institute for Parallel Processing at the B- garian Academy of Sciences. The conference was devoted to the 70th birthday anniversary of Professor Zahari Zlatev. The Bulgarian Academy of Sciences awarded him the Marin Drinov medal on ribbon for his outstanding results in environmental mat- matics and for his contributions to the Bulgarian mathematical society and the Academy of Sciences. The plenary invited speakers and lectures were: – P. Arbenz, “?Finite Element Analysis of Human Bone Structures” – Y. Efendiev, “Mixed Multiscale Finite Element Methods Using Limited Global Information” – U. Langer, “Fast Solvers for Non-Linear Time-Harmonic Problems” – T. Manteu?el, “First-Order System Least-Squares Approach to Resistive Magnetohydrodynamic Equations” – K. Sabelfeld, “Stochastic Simulation for Solving Random Boundary Value Problems and Some Applications” – F. Tro ¨ltzsch,“OnFinite ElementErrorEstimatesforOptimalControlPr- lems with Elliptic PDEs” – Z. Zlatev, “On Some Stability Properties of the Richardson Extrapolation Applied Together with the ?-method” The success of the conference and the present volume in particular are an outcome of the joint e?orts of many partnersfrom various institutions and or- nizations. Firstwe wouldlike to thank allthe membersofthe Scienti?c Comm- tee for their valuable contribution forming the scienti?c face of the conference, as well as for their help in reviewing contributed papers. We especially thank the organizers of the special sessions.

The two volume set LNCS 7133 and LNCS 7134 constitutes the thoroughly refereed post-conference proceedings of the 10th International Conference on Applied Parallel and Scientific Computing, PARA 2010, held in Reykjavík, Iceland, in June 2010. These volumes contain three keynote lectures, 29 revised papers and 45 minisymposia presentations arranged on the following topics: cloud computing, HPC algorithms, HPC programming tools, HPC in meteorology, parallel numerical algorithms, parallel computing in physics, scientific computing tools, HPC software engineering, simulations of atomic scale systems, tools and environments for accelerator based computational biomedicine, GPU computing, high performance computing interval methods, real-time access and processing of large data sets, linear algebra algorithms and software for multicore and hybrid architectures in honor of Fred Gustavson on his 75th birthday, memory and multicore issues in scientific computing - theory and praxis, multicore algorithms and implementations for application problems, fast PDE solvers and a posteriori error estimates, and scalable tools for high performance computing.

The Three-Volume-Set CCIS 323, 324, 325 (AsiaSim 2012) together with the Two-Volume-Set CCIS 326, 327 (ICSC 2012) constitutes the refereed proceedings of the Asia Simulation Conference, AsiaSim 2012, and the International Conference on System Simulation, ICSC 2012, held in Shanghai, China, in October 2012. The 267 revised full papers presented were carefully reviewed and selected from 906 submissions. The papers are organized in topical sections on modeling theory and technology; modeling and simulation technology on synthesized environment and virtual reality environment; pervasive computing and simulation technology; embedded computing and simulation technology; verification, validation and accreditation technology; networked modeling and simulation technology; modeling and simulation technology of continuous system, discrete system, hybrid system, and intelligent system; high performance computing and simulation technology; cloud simulation technology; modeling and simulation technology of complex system and open, complex, huge system; simulation based acquisition and virtual prototyping engineering technology; simulator; simulation language and intelligent simulation system; parallel and distributed software; CAD, CAE, CAM, CIMS, VP, VM, and VR; visualization; computing and simulation applications in science and engineering; computing and simulation applications in management, society and economics; computing and simulation applications in life and biomedical engineering; computing and simulation applications in energy and environment; computing and simulation applications in education; computing and simulation applications in military field; computing and simulation applications in medical field.