Visualization in scientific computing
Informations
- Type:
- article
- Auteurs:
- McCormick, Bruce H
- Pertinence:
-
Faible
- Référence:
- mccormick1988visualization
- Doi:
- Mots-clés:
- Url:
- https://www.sciencedirect.com/science/article/pii/S0065245808601680
- Date de publication:
- 12/1987
- Résumé:
- Abstract:
- Computational science and engineering (CS&E) describes a researcher's use of computers to simulate physical processes–to study phenomena too small, too large, too quick, too slow, or too dangerous to observe directly-in attempts to better understand our universe. Scientists employ the computer as a tool for discovery; it enables them to analyze the data to uncover new information. Computational scientists rely upon a host of high-volume data sources in order to conduct their research. However, they are deluged by the flood of data generated. Using an exclusively numerical format, the human brain cannot interpret gigabytes of data each day, so much information now goes to waste. It is impossible for users to ever quantitatively examine more than a tiny fraction of the solution; that is, it is impossible to investigate the qualitative global nature of numeric solutions. Therefore, the ability to visualize complex computations and simulations is absolutely essential to ensure the integrity of analyses, to provoke insights, and to communicate those insights with others. The chapter focuses on visualization. It is a method of computing that gives visual form to complex data. The growing importance of CS&E, especially with supercomputer capabilities, is creating a commensurate need for more sophisticated visual representations of natural phenomena across time. This requires the development of new tool sets for image generation, visual communication, and analysis. The chapter discusses examples of scientific-visualization for facilitating CS&E research specifically in the fields of planetary sciences, molecular modeling, mathematics, and medical Imaging. The chapter also highlights the current limitations and bottlenecks in visualization technology, focusing on software limitations, data management limitation, hardware limitations, educational limitations, and communication and publication limitation.
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Citations
1 articles
| Titre | Type | Pertinence | Auteurs | Date Publication | Références | Citations | Actions |
|---|---|---|---|---|---|---|---|
| Datavis: a visual programming language for scientific visualization | inproceedings | Moyenne | Hils, Daniel D | 12/1990 | 3 | 1 |
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