Toward ecosystem modeling on computing grids

Dali Wang; Eric Carr; Louis J. Gross; Michael W. Berry

doi:10.1109/MCSE.2005.104

Toward ecosystem modeling on computing grids

Dali Wang
, Eric Carr
, Louis J. Gross
, Michael W. Berry

Earth Systems Modeling

Research output: Contribution to journal › Review article › peer-review

15 Scopus citations

Abstract

Grid computing offers great promise for large-scale ecosystem modeling that potentially lead to better understanding, control, and management of natural resources. A prototype framework and generic software architecture provide increased interoperability and productivity for spatially explicit ecosystem modeling on heterogeneous grids. The scalability of integrated ecosystem simulation depends on the inherited relationship between individual ecological models and appropriate implementations of parallel communication libraries dedicated for ecosystem simulation. The university of Tennessee, with the support of the US National Science Foundation, established an intracampus grid to provide researchers the capability to develop new computational science methods in ecology, medicine, and materials science. This provide a technological and organizational microcosm in which the key research challenge underlying grid based computing can be attacked with good communication and control.

Original language	English
Pages (from-to)	44-51
Number of pages	8
Journal	Computing in Science and Engineering
Volume	7
Issue number	5
DOIs	https://doi.org/10.1109/MCSE.2005.104
State	Published - Sep 2005

Funding

The US National Science Foundation supported this research under grant number DEB-0219269. The NSF also supports the University of Tennessee’s Scalable Intracampus Research Grid (SInRG) project through CISE Research Infrastructure Award EIA-9972889.

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10.1109/MCSE.2005.104

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abstract = "Grid computing offers great promise for large-scale ecosystem modeling that potentially lead to better understanding, control, and management of natural resources. A prototype framework and generic software architecture provide increased interoperability and productivity for spatially explicit ecosystem modeling on heterogeneous grids. The scalability of integrated ecosystem simulation depends on the inherited relationship between individual ecological models and appropriate implementations of parallel communication libraries dedicated for ecosystem simulation. The university of Tennessee, with the support of the US National Science Foundation, established an intracampus grid to provide researchers the capability to develop new computational science methods in ecology, medicine, and materials science. This provide a technological and organizational microcosm in which the key research challenge underlying grid based computing can be attacked with good communication and control.",

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AU - Gross, Louis J.

AU - Berry, Michael W.

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AB - Grid computing offers great promise for large-scale ecosystem modeling that potentially lead to better understanding, control, and management of natural resources. A prototype framework and generic software architecture provide increased interoperability and productivity for spatially explicit ecosystem modeling on heterogeneous grids. The scalability of integrated ecosystem simulation depends on the inherited relationship between individual ecological models and appropriate implementations of parallel communication libraries dedicated for ecosystem simulation. The university of Tennessee, with the support of the US National Science Foundation, established an intracampus grid to provide researchers the capability to develop new computational science methods in ecology, medicine, and materials science. This provide a technological and organizational microcosm in which the key research challenge underlying grid based computing can be attacked with good communication and control.

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IS - 5

ER -

Toward ecosystem modeling on computing grids

Abstract

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