Modern Software Tools for Scientific Computing

Modern Software Tools for Scientific Computing PDF Author: A. Bruaset
Publisher: Springer Science & Business Media
ISBN: 1461219868
Category : Computers
Languages : en
Pages : 387

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Book Description
Looking back at the years that have passed since the realization of the very first electronic, multi-purpose computers, one observes a tremendous growth in hardware and software performance. Today, researchers and engi neers have access to computing power and software that can solve numerical problems which are not fully understood in terms of existing mathemati cal theory. Thus, computational sciences must in many respects be viewed as experimental disciplines. As a consequence, there is a demand for high quality, flexible software that allows, and even encourages, experimentation with alternative numerical strategies and mathematical models. Extensibil ity is then a key issue; the software must provide an efficient environment for incorporation of new methods and models that will be required in fu ture problem scenarios. The development of such kind of flexible software is a challenging and expensive task. One way to achieve these goals is to in vest much work in the design and implementation of generic software tools which can be used in a wide range of application fields. In order to provide a forum where researchers could present and discuss their contributions to the described development, an International Work shop on Modern Software Tools for Scientific Computing was arranged in Oslo, Norway, September 16-18, 1996. This workshop, informally referred to as Sci Tools '96, was a collaboration between SINTEF Applied Mathe matics and the Departments of Informatics and Mathematics at the Uni versity of Oslo.

Modern Software Tools for Scientific Computing

Modern Software Tools for Scientific Computing PDF Author: A. Bruaset
Publisher: Springer Science & Business Media
ISBN: 1461219868
Category : Computers
Languages : en
Pages : 387

Get Book

Book Description
Looking back at the years that have passed since the realization of the very first electronic, multi-purpose computers, one observes a tremendous growth in hardware and software performance. Today, researchers and engi neers have access to computing power and software that can solve numerical problems which are not fully understood in terms of existing mathemati cal theory. Thus, computational sciences must in many respects be viewed as experimental disciplines. As a consequence, there is a demand for high quality, flexible software that allows, and even encourages, experimentation with alternative numerical strategies and mathematical models. Extensibil ity is then a key issue; the software must provide an efficient environment for incorporation of new methods and models that will be required in fu ture problem scenarios. The development of such kind of flexible software is a challenging and expensive task. One way to achieve these goals is to in vest much work in the design and implementation of generic software tools which can be used in a wide range of application fields. In order to provide a forum where researchers could present and discuss their contributions to the described development, an International Work shop on Modern Software Tools for Scientific Computing was arranged in Oslo, Norway, September 16-18, 1996. This workshop, informally referred to as Sci Tools '96, was a collaboration between SINTEF Applied Mathe matics and the Departments of Informatics and Mathematics at the Uni versity of Oslo.

Advances in Software Tools for Scientific Computing

Advances in Software Tools for Scientific Computing PDF Author: Hans P. Langtangen
Publisher: Springer Science & Business Media
ISBN: 3642571727
Category : Computers
Languages : en
Pages : 362

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Book Description
To make full use of the ever increasing hardware capabilities of modern com puters, it is necessary to speedily enhance the performance and reliability of the software as well, and often without having a suitable mathematical theory readily available. In the handling of more and more complex real-life numerical problems in all sorts of applications, a modern object-oriented de sign and implementation of software tools has become a crucial component. The considerable challenges posed by the demand for efficient object-oriented software in all areas of scientific computing make it necessary to exchange ideas and experiences from as many different sources as possible. Motivated by the success of the first meeting of this kind in Norway in 1996, we decided to organize another International Workshop on Modern Software Tools for Scientific Computing, often referred to as SciTools'98. This workshop took place in Oslo, Norway, September 14-16, 1998. The ob jective was again to provide an open forum for exchange and discussion of modern, state-of-the-art software techniques applied to challenging numerical problems. The organization was undertaken jointly by the research institute SINTEF Applied Mathematics, the Departments of Mathematics and Infor matics at the University of Oslo, and the company Numerical Objects AS.

Modern Softwaretools For Scientific Computing

Modern Softwaretools For Scientific Computing PDF Author: Erlend Arge
Publisher:
ISBN: 9788179921654
Category :
Languages : en
Pages : 392

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Book Description
This book surveys some recent advances in the development of software tools for scientific computing. Presented here are 17 carefully selected and referred chapters originally presented at the SciTools Workshop in Oslo, Norway. The chapters emphasize the design of large software codes, computational efficiency, object-oriented programming in scientific computing.

Modern Software Tools for Scientific Computing

Modern Software Tools for Scientific Computing PDF Author: Erlend Arge
Publisher:
ISBN: 9783764339746
Category : Computer software
Languages : en
Pages : 380

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Book Description
Surveys some recent advances in 17 selected and refereed papers from an international workshop held in Oslo, Norway in September 1996. In general they cover computational differential equations, computational geometry, and software development. Among the specific topics are object-oriented solvers for initial value problems, the efficient implementation of multilevel adaptive methods, object-oriented scattered data modelling with Siscat, and automating the debugging of large numerical codes. Annotation copyrighted by Book News, Inc., Portland, OR

Introduction to Scientific and Technical Computing

Introduction to Scientific and Technical Computing PDF Author: Frank T. Willmore
Publisher: CRC Press
ISBN: 1315351854
Category : Computers
Languages : en
Pages : 266

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Book Description
Created to help scientists and engineers write computer code, this practical book addresses the important tools and techniques that are necessary for scientific computing, but which are not yet commonplace in science and engineering curricula. This book contains chapters summarizing the most important topics that computational researchers need to know about. It leverages the viewpoints of passionate experts involved with scientific computing courses around the globe and aims to be a starting point for new computational scientists and a reference for the experienced. Each contributed chapter focuses on a specific tool or skill, providing the content needed to provide a working knowledge of the topic in about one day. While many individual books on specific computing topics exist, none is explicitly focused on getting technical professionals and students up and running immediately across a variety of computational areas.

The Architecture of Scientific Software

The Architecture of Scientific Software PDF Author: Ronald F. Boisvert
Publisher: Springer
ISBN: 0387354077
Category : Computers
Languages : en
Pages : 360

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Book Description
Scientific applications involve very large computations that strain the resources of whatever computers are available. Such computations implement sophisticated mathematics, require deep scientific knowledge, depend on subtle interplay of different approximations, and may be subject to instabilities and sensitivity to external input. Software able to succeed in this domain invariably embeds significant domain knowledge that should be tapped for future use. Unfortunately, most existing scientific software is designed in an ad hoc way, resulting in monolithic codes understood by only a few developers. Software architecture refers to the way software is structured to promote objectives such as reusability, maintainability, extensibility, and feasibility of independent implementation. Such issues have become increasingly important in the scientific domain, as software gets larger and more complex, constructed by teams of people, and evolved over decades. In the context of scientific computation, the challenge facing mathematical software practitioners is to design, develop, and supply computational components which deliver these objectives when embedded in end-user application codes. The Architecture of Scientific Software addresses emerging methodologies and tools for the rational design of scientific software, including component integration frameworks, network-based computing, formal methods of abstraction, application programmer interface design, and the role of object-oriented languages. This book comprises the proceedings of the International Federation for Information Processing (IFIP) Conference on the Architecture of Scientific Software, which was held in Ottawa, Canada, in October 2000. It will prove invaluable reading for developers of scientific software, as well as for researchers in computational sciences and engineering.

Software Engineering for Science

Software Engineering for Science PDF Author: Jeffrey C. Carver
Publisher: CRC Press
ISBN: 1315351927
Category : Computers
Languages : en
Pages : 296

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Book Description
Software Engineering for Science provides an in-depth collection of peer-reviewed chapters that describe experiences with applying software engineering practices to the development of scientific software. It provides a better understanding of how software engineering is and should be practiced, and which software engineering practices are effective for scientific software. The book starts with a detailed overview of the Scientific Software Lifecycle, and a general overview of the scientific software development process. It highlights key issues commonly arising during scientific software development, as well as solutions to these problems. The second part of the book provides examples of the use of testing in scientific software development, including key issues and challenges. The chapters then describe solutions and case studies aimed at applying testing to scientific software development efforts. The final part of the book provides examples of applying software engineering techniques to scientific software, including not only computational modeling, but also software for data management and analysis. The authors describe their experiences and lessons learned from developing complex scientific software in different domains. About the Editors Jeffrey Carver is an Associate Professor in the Department of Computer Science at the University of Alabama. He is one of the primary organizers of the workshop series on Software Engineering for Science (http://www.SE4Science.org/workshops). Neil P. Chue Hong is Director of the Software Sustainability Institute at the University of Edinburgh. His research interests include barriers and incentives in research software ecosystems and the role of software as a research object. George K. Thiruvathukal is Professor of Computer Science at Loyola University Chicago and Visiting Faculty at Argonne National Laboratory. His current research is focused on software metrics in open source mathematical and scientific software.

Accuracy and Reliability in Scientific Computing

Accuracy and Reliability in Scientific Computing PDF Author: Bo Einarsson
Publisher: SIAM
ISBN: 9780898718157
Category : Science
Languages : en
Pages : 361

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Book Description
Numerical software is used to test scientific theories, design airplanes and bridges, operate manufacturing lines, control power plants and refineries, analyze financial derivatives, identify genomes, and provide the understanding necessary to derive and analyze cancer treatments. Because of the high stakes involved, it is essential that results computed using software be accurate, reliable, and robust. Unfortunately, developing accurate and reliable scientific software is notoriously difficult. This book investigates some of the difficulties related to scientific computing and provides insight into how to overcome them and obtain dependable results. The tools to assess existing scientific applications are described, and a variety of techniques that can improve the accuracy and reliability of newly developed applications is discussed. Accuracy and Reliability in Scientific Computing can be considered a handbook for improving the quality of scientific computing. It will help computer scientists address the problems that affect software in general as well as the particular challenges of numerical computation: approximations occurring at all levels, continuous functions replaced by discretized versions, infinite processes replaced by finite ones, and real numbers replaced by finite precision numbers. Divided into three parts, it starts by illustrating some of the difficulties in producing robust and reliable scientific software. Well-known cases of failure are reviewed and the what and why of numerical computations are considered. The second section describes diagnostic tools that can be used to assess the accuracy and reliability of existing scientific applications. In the last section, the authors describe a variety of techniques that can be employed to improve the accuracy and reliability of newly developed scientific applications. The authors of the individual chapters are international experts, many of them members of the IFIP Working Group on Numerical Software.

Introduction to High Performance Scientific Computing

Introduction to High Performance Scientific Computing PDF Author: David L. Chopp
Publisher: SIAM
ISBN: 1611975646
Category : Mathematics
Languages : en
Pages : 468

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Book Description
Based on a course developed by the author, Introduction to High Performance Scientific Computing introduces methods for adding parallelism to numerical methods for solving differential equations. It contains exercises and programming projects that facilitate learning as well as examples and discussions based on the C programming language, with additional comments for those already familiar with C++. The text provides an overview of concepts and algorithmic techniques for modern scientific computing and is divided into six self-contained parts that can be assembled in any order to create an introductory course using available computer hardware. Part I introduces the C programming language for those not already familiar with programming in a compiled language. Part II describes parallelism on shared memory architectures using OpenMP. Part III details parallelism on computer clusters using MPI for coordinating a computation. Part IV demonstrates the use of graphical programming units (GPUs) to solve problems using the CUDA language for NVIDIA graphics cards. Part V addresses programming on GPUs for non-NVIDIA graphics cards using the OpenCL framework. Finally, Part VI contains a brief discussion of numerical methods and applications, giving the reader an opportunity to test the methods on typical computing problems.

Parallel Processing for Scientific Computing

Parallel Processing for Scientific Computing PDF Author: Michael A. Heroux
Publisher: SIAM
ISBN: 9780898718133
Category : Computers
Languages : en
Pages : 421

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Book Description
Parallel processing has been an enabling technology in scientific computing for more than 20 years. This book is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, computer scientists, and computational scientists focus on to make parallel processing effective for scientific problems. Presently, the impact of parallel processing on scientific computing varies greatly across disciplines, but it plays a vital role in most problem domains and is absolutely essential in many of them. Parallel Processing for Scientific Computing is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth provides a sampling of applications that require parallel computing for scaling to solve larger and realistic models that can advance science and engineering.