Riassunto:
Enabling Technologies for Computational Science assesses future application computing needs, identifies research directions in problem-solving environments (PSEs), addresses multi-disciplinary environments operating on the Web, proposes methodologies and software architectures for building adaptive and human-centered PSEs, and describes the role of symbolic computing in scientific and engineering PSEs. The book also includes an extensive bibliography of over 400 references.
Enabling Technologies for Computational Science illustrates the extremely broad and interdisciplinary nature of the creation and application of PSEs. Authors represent academia, government laboratories and industry, and come from eight distinct disciplines (chemical engineering, computer science, ecology, electrical engineering, mathematics, mechanical engineering, psychology and wood sciences). This breadth and diversity extends into the computer science aspects of PSEs. These papers deal with topics such as artificial intelligence, computer-human interaction, control, data mining, graphics, language design and implementation, networking, numerical analysis, performance evaluation, and symbolic computing.
Enabling Technologies for Computational Science provides an assessment of the state of the art and a road map to the future in the area of problem-solving environments for scientific computing. This book is suitable as a reference for scientists from a variety of disciplines interested in using PSEs for their research.
Contenuti:
Contributing Authors. Preface. Part I: Problem Solving Environments: Enabling Technology for Computational Science. 1. Future Challenges for Scientific Simulation; J.R. Rice. 2. Workshop on Scientific Knowledge, Information and Computing; R. Bramley, et al. 3. Scalable Software Libraries and PSEs; J.R. Rice, R.F. Boisvert. 4. The 21st Century Emergence of the MPSE; A.J. Baker. 5. PPK: Towards a Kernel for Building PSEs; S. Weerawarana, et al. 6. Managing Specificity and Generality in PSEs; D. Dabdub, et al. 7. Toward a Human Centered Scientific Problem Solving Environment; T.T. Hewett, J.L. DePaul. 8. Problem Solving Environments and Symbolic Computing; R.J. Fateman. Part II: Domain Specific PSEs: Characteristics for Computational Science. 9. SciNapse: A Problem Solving Environment for PDEs; R.L. Akers, et al. 10. The Linear System Analyzer; D. Gannon, et al. 11. VECFEM - Solver for Non-linear Partial Differential Equations; L. Grosz. 12. Khoros: An IDE for Scientific Computing and Visualization; D. Argiro, et al. 13. Workbench for Interactive Simulation of Ecosystems; R.G. Knox, et al. 14. PELLPACK: A PSE for PDE Applications on Multicomputer Platforms; E.N. Houstis. 15. WBCSim: A Prototype PSE for Wood-Based Composites Simulations; A. Goel, et al. Part III: Frameworks, Middleware and Software: Enabling and Delivering the Problem Solving Power. 16. A Problem Solving Environment for Network Centric Computing; S. Hariri, et al. 17. Multiagent Recommender Systems in Networked Scientific Computing; A. Joshi, et al. 18. Performance of Network-Based Problem-Solving Environments; R.I. Balay, et al. 19. A Java Framework for Internet Distributed Computations. 20. Network based PSEs for PDE Computing; S. Markus, et al. 21. Data Mining Environment for Modeling Performance of Scientific Software; E.N. Houstis. 22. TechTALK: A Web Based System for Mathematical Collaboration; Y.N. Lakshman, et al. Part IV: Steering, Generation and Validation: Tools for Building and Using PSEs. 23. Visual Steering of the Simulation Process: NCAS; S. Kawata, et al. 24. Softlab: A Virtual Laboratory Framework for Computational Science; A.C. Catlin, et al. 25. Design Issues in a MATLAB-based Environment for Numerical Programs; L. DeRose, et al. 26. The Ctadel Application Driver; R. van Engelen, et al. 27. Visual Steering of Grid Generation; Y. Zheng, et al. 28. Aquarels: A PSE for Validating Scientific Software; O. Beaumont, et al. Part V: A PSE Bibliography. References. Index.
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