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Full Description
Taking an interdisciplinary approach, this new book provides a modern introduction to scientific computing, exploring numerical methods, computer technology, and their interconnections, which are treated with the goal of facilitating scientific research across all disciplines. Each chapter provides an insightful lesson and viewpoints from several subject areas are often compounded within a single chapter. Written with an eye on usefulness, longevity, and breadth, Lessons in Scientific Computing will serve as a "one stop shop" for students taking a unified course in scientific computing, or seeking a single cohesive text spanning multiple courses.
Features:
Provides a unique combination of numerical analysis, computer programming, and computer hardware in a single text
Includes essential topics such as numerical methods, approximation theory, parallel computing, algorithms, and examples of computational discoveries in science
Not wedded to a specific programming language
Contents
1. Analytical and Numerical Solutions 2. A Few Concepts from Numerical Analysis 3. Roundoff and Number Representation 4. Programming Languages and Tools 5. Sample Problems; Building Conclusions 6. Approximation Theory 7. Other Common Computational Methods 8. Performance Basics and Computer Architectures 9. High-Performance and Parallel Computing 10. The Operation Count; Numerical Linear Algebra 11. Random Numbers and Stochastic Methods 12. Algorithms, Data Structures, and Complexity 13. Data 14. Building Programs for Computation and Data Analysis 15. Crash Course on Partial Differential Equiations 16. Reformulated Problems
