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A Generic Task-Farming Framework for Reservoir Analysis in a Grid Environment
Columbus, Ohio August 14-August 18
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPPW.2006.82006 International Conference on Para ...
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Santiago Pena, Louisiana State University, USA
Dayong Huang, Louisiana State University, USA
Zhou Lei, Louisiana State University, USA
Gabrielle Allen, Louisiana State University, USA
Xin Li, Louisiana State University, USA
Chris D. White, Louisiana State University, USA
The vast majority of research projects involving Grid Computing have focused on the development and standardization of the middleware that allows Grids to function. Despite the maturity of the middleware as the Grid core, the actual application of Grids to solving concrete problems is far from being a common practice, much less a standard one. In this context, we present ResGrid, a Grid-aware toolkit for reservoir uncertainty analysis. With the help of ResGrid, a reservoir engineer can transparently take advantage of Grid resources and services for compute-intensive and data-intensive uncertainty analysis while achieving a better understanding of multiphase reservoir modeling. ResGrid improves the efficiency of reservoir analysis, and its flexible architecture allows its utilization by other application areas such as coastal modeling and climate simulations. ResGrid is our first step towards developing generic Grid-aware toolkits that could be applied to any science in a costand time-efficient manner.
Citation:
Santiago Pena, Dayong Huang, Zhou Lei, Gabrielle Allen, Xin Li, Chris D. White, "A Generic Task-Farming Framework for Reservoir Analysis in a Grid Environment," icppw, pp.426-434, 2006 International Conference on Parallel Processing Workshops (ICPPW'06), 2006
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