Recently, computational simulation has become a third approach-along with theory and laboratory simulation-to studying and solving scientific problems. In this approach, a computer equipped with problem-solving software tools may represent a virtual laboratory in which researchers can build a model for a given problem and run it under varying conditions. These increasingly complex computational methodologies require sophisticated models and techniques, and vice versa. The authors explain how developing and validating complex models will increasingly depend on significant advances in experimental and testing techniques. High-performance parallel computers gave researchers the ability to implement inherently parallel techniques such as cellular automata (CA), neural networks, and genetic algorithms-significant new mathematical models for describing complex scientific phenomena.
Cellular processing tools for high-performance simulation / Talia, Domenico. - In: COMPUTER. - ISSN 0018-9162. - 33:9(2000), pp. 44-+.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
Titolo: | Cellular processing tools for high-performance simulation |
Autori: | |
Data di pubblicazione: | 2000 |
Rivista: | |
Citazione: | Cellular processing tools for high-performance simulation / Talia, Domenico. - In: COMPUTER. - ISSN 0018-9162. - 33:9(2000), pp. 44-+. |
Abstract: | Recently, computational simulation has become a third approach-along with theory and laboratory simulation-to studying and solving scientific problems. In this approach, a computer equipped with problem-solving software tools may represent a virtual laboratory in which researchers can build a model for a given problem and run it under varying conditions. These increasingly complex computational methodologies require sophisticated models and techniques, and vice versa. The authors explain how developing and validating complex models will increasingly depend on significant advances in experimental and testing techniques. High-performance parallel computers gave researchers the ability to implement inherently parallel techniques such as cellular automata (CA), neural networks, and genetic algorithms-significant new mathematical models for describing complex scientific phenomena. |
Handle: | http://hdl.handle.net/20.500.11770/142551 |
Appare nelle tipologie: | 1.1 Articolo in rivista |