Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Scientific Computing and Simulation Science
- 2 Basic Concepts and Tools
- 3 Approximation
- 4 Roots and Integrals
- 5 Explicit Discretizations
- 6 Implicit Discretizations
- 7 Relaxation: Discretization and Solvers
- 8 Propagation: Numerical Diffusion and Dispersion
- 9 Fast Linear Solvers
- 10 Fast Eigensolvers
- A C++ Basics
- B MPI Basics
- Bibliography
- Index
1 - Scientific Computing and Simulation Science
Published online by Cambridge University Press: 05 October 2013
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Scientific Computing and Simulation Science
- 2 Basic Concepts and Tools
- 3 Approximation
- 4 Roots and Integrals
- 5 Explicit Discretizations
- 6 Implicit Discretizations
- 7 Relaxation: Discretization and Solvers
- 8 Propagation: Numerical Diffusion and Dispersion
- 9 Fast Linear Solvers
- 10 Fast Eigensolvers
- A C++ Basics
- B MPI Basics
- Bibliography
- Index
Summary
WHAT IS SIMULATION?
Science and engineering have undergone a major transformation at the research level as well as at the development and technology level. The modern scientist and engineer spend more and more time in front of a laptop, a workstation, or a parallel supercomputer and less and less time in the physical laboratory or in the workshop. The virtual wind tunnel and the virtual biology laboratory are not a thing of the future; they are here! The old approach of “cut and try” has been replaced by “simulate and analyze” in several key technological areas such as aerospace applications, synthesis of new materials, design of new drugs, and chip processing and microfabrication. The new discipline of nanotechnology will be based primarily on large-scale computations and numerical experiments. The methods of scientific analysis and engineering design are changing continuously, affecting both our approach to the phenomena that we study as well as the range of applications that we address. Whereas there is an abundance of software available to be used as almost a “black box,” working in new application areas requires good knowledge of fundamentals and mastering of effective new tools.
In the classical scientific approach, the physical system is first simplified and set in a form that suggests what type of phenomena and processes may be important and, correspondingly, what experiments are to be conducted. In the absence of any known type of governing equations, dimensional inter dependence between physical parameters can guide laboratory experiments in identifying key parametric studies.
- Type
- Chapter
- Information
- Parallel Scientific Computing in C++ and MPIA Seamless Approach to Parallel Algorithms and their Implementation, pp. 1 - 9Publisher: Cambridge University PressPrint publication year: 2003