MODERN SOFTWARE TOOLS FOR SCIENTIFIC COMPUTING

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.

I. Computational Differential Equations.- 1 The SCIRun Computational Steering Software System.- 1.1 Introduction.- 1.2 Requirements of SCIRun as a Computational Steering System.- 1.3 Components of SCIRun.- 1.4 The Datatypes Library.- 1.5 Dataflow.- 1.6 Steering in a Dataflow System.- 1.7 Modules.- 1.8 Applications of SCIRun in Computational Medicine.- 1.9 Summary.- 1.10 Future Work.- 1.11 References.- 1.12 Software Appendix.- 2 Object-Oriented Solvers for Initial Value Problems.- 2.1 Introduction.- 2.2 Overview of the Code.- 2.3 Case Studies: New algorithms.- 2.4 Comparison with Classical Solvers.- 2.5 Conclusions.- 2.6 References.- 3 SPRINT2D Software for Convection Dominated PDEs.- 3.1 Introduction.- 3.2 The SPRINT2D Software.- 3.3 Mesh Generation and Adaptivity.- 3.4 A PSE for SPRINT2D.- 3.5 Case Studies.- 3.6 Conclusions.- 3.7 References.- 4 Electrochemical Modelling and Software Genericity.- 4.1 Introduction.- 4.2 Electrochemical Modelling.- 4.3 A Generalized Approach to Numerical Modelling.- 4.4 Abstractions.- 4.5 Critical Remarks.- 4.6 Conclusions.- 4.7 References.- 5 An Object-Oriented Adaptive Finite Element Code: Design Issues and Applications in Hyperthermia Treatment Planning.- 5.1 Introduction.- 5.2 Code Structure.- 5.3 Applications in Hyperthermia Treatment Planning.- 5.4 Concluding Remarks.- 5.5 References.- 6 On the Efficient Implementation of Multilevel Adaptive Methods.- 6.1 Introduction.- 6.2 Multilevel Implementations.- 6.3 Data Abstraction Concepts for Multilevel Adaptive Methods.- 6.4 Efficiency.- 6.5 Abstract Mesh Data Structures.- 6.6 Patch-Adaptive Multigrid.- 6.7 Conclusions.- 6.8 References.- 7 Finite Element Kernel with Metaobject Protocol.- 7.1 Introduction.- 7.2 Example Problems.- 7.3 Procedural Approach.- 7.4 Object-Oriented Approach.- 7.5 Algorithm-Oriented Approach.- 7.6 Conclusions.- 7.7 References.- 8 Efficient Management of Parallelism in Object-Oriented Numerical Software Libraries.- 8.1 Introduction.- 8.2 The Message Passing Model for Programming Distributed-Memory Parallel Systems.- 8.3 Distributed Computational Objects.- 8.4 Six Guiding Principles.- 8.5 PETSc Design of Fundamental Objects.- 8.6 Sample Performance Results.- 8.7 Conclusion.- 8.8 References.- 9 Object-Oriented Construction of Parallel PDE Solvers.- 9.1 Introduction.- 9.2 The Object-Oriented Approach.- 9.3 Overview of Cogito.- 9.4 Case Study 1: Application of Cogito/Grid.- 9.5 Case Study 2: Application of Cogito/Solver.- 9.6 Cogito for Implicit Methods.- 9.7 Validation of Cogito.- 9.8 Concluding Remarks.- 9.9 References.- 10 Modern Software Techniques in Computational Finance.- 10.1 Introduction.- 10.2 Option Computations.- 10.3 Software Design Issues in Option Valuation.- 10.4 FINANZIA Implementation and Examples.- 10.5 Future Extensions.- 10.6 Conclusions.- 10.7 References.- 11 Increasing the Efficiency and Reliability of Software Development for Systems of PDEs.- 11.1 Introduction.- 11.2 A Plastic Forming Process.- 11.3 The Basic Ideas.- 11.4 Diffpack.- 11.5 Systems of PDEs.- 11.6 Extensions of the Concept.- 11.7 Other Applications.- 11.8 Another Application of the Flexible Design.- 11.9 Concluding Remarks.- 11.10 References.- II. Computational Geometry.- 12 Object Oriented Surface Design.- 12.1 Overview.- 12.2 Geometrical Abstractions.- 12.3 Data Structures.- 12.4 Splines.- 12.5 Surfaces.- 12.6 Refiners.- 12.7 Applications.- 12.8 Development Environment.- 12.9 References.- 13 Object-Oriented Scattered Data Modelling with Siscat.- 13.1 Introduction.- 13.2 A Cartographic Model Problem.- 13.3 The Basic Surface Hierarchy in Siscat.- 13.4 Aspects of Basic Methods.- 13.5 Composite Methods.- 13.6 References.- III. Software Development.- 14 Is the Quality of Numerical Subroutine Code Improving?.- 14.1 Introduction.- 14.2 Software Metrics.- 14.3 A Comparison of Freely Available Packages.- 14.4 CALGO Fortran Codes.- 14.5 Conclusion.- 14.6 References.- 15 Object-Oriented Redesign of a Real-World Fortran 77 Solver.- 15.1 Introduction.- 15.2 The SEMPA Project.- 15.3 The CFD Program.- 15.4 Analysis and Redesign of the Solver.- 15.5 Original and New Module Comparison.- 15.6 Discussion of the Approach.- 15.7 References.- 16 Automating the Debugging of Large Numerical Codes.- 16.1 Introduction.- 16.2 Comparative Debugging.- 16.3 Examples of Use.- 16.4 The Wizard.- 16.5 Conclusion.- 16.6 References.- 17 The TAMPR Program Transformation System: Simplifying the Development of Numerical Software.- 17.1 Introduction.- 17.2 Some TAMPR Applications.- 17.3 The TAMPR Approach to Program Transformation.- 17.4 Example of the TAMPR Approach to Program Transformation.- 17.5 Conclusion.- 17.6 References.- List of Contributors.