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Decreasing Computational Time of Urban Cellular Automata Through Model Portability.

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Title: Decreasing Computational Time of Urban Cellular Automata Through Model Portability.
Authors: Dietzel, Charles1 dietzel@geog.ucsb.edu, Clarke, Keith2 kclarke@geog.ucsb.edu
Source: GeoInformatica. Jun2006, Vol. 10 Issue 2, p197-211. 15p. 5 Charts, 2 Graphs.
Subjects: Cellular automata, Sequential machine theory, Software compatibility, Computer operating systems, Electronic data processing, Economic geography, Mathematical models, Structural optimization
Abstract: This paper investigates how portability of a model between different computer operating systems can lead to increased efficiency in code execution. The portability problem is not a trivial one, as many geographic models are designed to be run inside a set environment (Unix, Solaris, Linux, and Windows), and are further limited by hardware constraints. The SLEUTH urban growth model [K.C Clarke, S. Hoppen, and L. Gaydos. “A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area”, Environment and Planning B, 24:247–261, 1997.] was implemented under three different operating systems (Solaris, Linux, and Windows). Results suggest that the model's performance is optimized by porting it from its original environment (Unix/Solaris) to Linux or Windows where faster processors are available. While the results show optimization of model performance, there are some suggestions of computational bottlenecks that may eventually limit the increased performance of the model. Regardless, the research demonstrates that the portability of a model can lead to not only to a decrease in computation time, but may increase the viability in practical applications and attract a wider user base. [ABSTRACT FROM AUTHOR]
Copyright of GeoInformatica is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="DE" term="%22Cellular+automata%22">Cellular automata</searchLink><br /><searchLink fieldCode="DE" term="%22Sequential+machine+theory%22">Sequential machine theory</searchLink><br /><searchLink fieldCode="DE" term="%22Software+compatibility%22">Software compatibility</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+operating+systems%22">Computer operating systems</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Economic+geography%22">Economic geography</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+optimization%22">Structural optimization</searchLink>
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  Data: This paper investigates how portability of a model between different computer operating systems can lead to increased efficiency in code execution. The portability problem is not a trivial one, as many geographic models are designed to be run inside a set environment (Unix, Solaris, Linux, and Windows), and are further limited by hardware constraints. The SLEUTH urban growth model [K.C Clarke, S. Hoppen, and L. Gaydos. “A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area”, Environment and Planning B, 24:247–261, 1997.] was implemented under three different operating systems (Solaris, Linux, and Windows). Results suggest that the model's performance is optimized by porting it from its original environment (Unix/Solaris) to Linux or Windows where faster processors are available. While the results show optimization of model performance, there are some suggestions of computational bottlenecks that may eventually limit the increased performance of the model. Regardless, the research demonstrates that the portability of a model can lead to not only to a decrease in computation time, but may increase the viability in practical applications and attract a wider user base. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of GeoInformatica is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10707-006-7579-0
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        Text: English
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      – SubjectFull: Sequential machine theory
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      – SubjectFull: Software compatibility
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