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Einarsson, Bo
Publications (3 of 3) Show all publications
Einarsson, B., Hanson, R. & Hopkins, T. (2009). Standardized mixed language programming for Fortran and C. ACM SIGPLAN Fortran Forum, 28(3), 8-22
Open this publication in new window or tab >>Standardized mixed language programming for Fortran and C
2009 (English)In: ACM SIGPLAN Fortran Forum, ISSN 1061-7264, Vol. 28, no 3, p. 8-22Article in journal (Refereed) Published
Abstract [en]

Programmers have long practiced the matter of mixed language procedure calls. This is particularly true for the programming languages C and Fortran. The use of the alternate language often results in efficient running time or the effective use of human or other resources.

Prior to the Fortran 2003 standard there was silence about how the two languages interoperated. Before this release there existed a set of differing ad hoc methods for making the inter-language calls. These typically depended on the Fortran and C compilers. The newer Fortran standard provides an intrinsic module, iso_c_binding, that permits the languages to interoperate. There remain restrictions regarding interoperable data types.

This paper illustrates several programs that contain core exercises likely to be encountered by programmers. The source code is available from the first author's web site. Included is an illustration of a "trap" based on use of the ad hoc methods: A call from a C to a Fortran 2003 routine that passes a character in C to a character variable in Fortran results in a run-time error.

Place, publisher, year, edition, pages
New York: ACM, 2009
Keywords
Fortran, C
National Category
Software Engineering
Identifiers
urn:nbn:se:liu:diva-52950 (URN)
Available from: 2010-01-14 Created: 2010-01-14 Last updated: 2018-01-12
Einarsson, B. (Ed.). (2005). Accuracy and Reliability in Scientific Computing. Philadelphia: SIAM
Open this publication in new window or tab >>Accuracy and Reliability in Scientific Computing
2005 (English)Collection (editor) (Other academic)
Abstract [en]

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. Accuracy and Reliability in Scientific Computing contains condensed information on the main features of six major programming languages - Ada, C, C++, Fortran, Java, and Python - and the INTLAB toolbox of the MATLAB software and the PRECISE toolbox of Fortran are discussed in detail. This book has an accompanying website, www.nsc.liu.se/wg25/book/, with codes, links, color versions of some illustrations, and additional material.

Place, publisher, year, edition, pages
Philadelphia: SIAM, 2005. p. 338
Series
Software-Environments-Tools ; SE18
Keywords
accuracy, numerical software, reliability
National Category
Mathematics
Identifiers
urn:nbn:se:liu:diva-28879 (URN)14075 (Local ID)0-89871-584-9 (ISBN)978-0-89871-584-2 (ISBN)14075 (Archive number)14075 (OAI)
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2013-09-27Bibliographically approved
Chubarov, L., Fedotova, Z., Shokin, Y. & Einarsson, B. (2000). Comparative analysis of nonlinear dispersive shallow water models. International journal of computational fluid dynamics (Print), 14(1), 55-73
Open this publication in new window or tab >>Comparative analysis of nonlinear dispersive shallow water models
2000 (English)In: International journal of computational fluid dynamics (Print), ISSN 1061-8562, E-ISSN 1029-0257, Vol. 14, no 1, p. 55-73Article in journal (Refereed) Published
Abstract [en]

The results of comparative analysis of some nonlinear dispersive models of shallow water are presented. The aim is to find their individual properties relevant for the numerical solution of some model problems of long wave transformation over submerged obstacles The study considers basic properties of the listed models and their numerical implementation. Computations are obtained compared with the analytical solution and experimental data. Attention is primarily focused on the models suggested by Peregrine (1967), Zheleznyak and Pelinovsky (1985), Kim, Reid, Whitaker (1988), Fedotova and Pashkova (1997). Also classical equations of shallow water are considered in both linear and nonlinear approximations.

Keywords
shallow water models, nonlinear dispersive models, finite-difference schemes, wave interaction, solitary wave
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-49463 (URN)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2017-12-12
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