Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-06T01:03:30.541Z Has data issue: false hasContentIssue false

1 - Scientific Computing and Simulation Science

Published online by Cambridge University Press:  05 October 2013

George Em Karniadakis
Affiliation:
Brown University, Rhode Island
Robert M. Kirby II
Affiliation:
University of Utah
Get access

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 The old approach of “cut and try” has been replaced by “simulate and analyze” in several key technological areas such as aerospace applications, synthesis of new materials, design of new drugs, and chip processing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 MPI
A Seamless Approach to Parallel Algorithms and their Implementation
, pp. 1 - 9
Publisher: Cambridge University Press
Print publication year: 2003

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×