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Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06)
ResGrid: A Grid-aware Toolkit for Reservoir Uncertainty Analysis
Singapore
May 16-May 19
ISBN: 0-7695-2585-7
Zhou Lei, Louisiana State University, USA
Dayong Huang, Louisiana State University, USA
Archit Kulshrestha, Louisiana State University, USA
Santiago Pena, Louisiana State University, USA
Gabrielle Allen, Louisiana State University, USA
Xin Li, Lousiana State University, USA
Christopher White, Louisiana State University, USA
Richard Duff, Louisiana State University, USA
John R. Smith, Louisiana State University, USA
Subhash Kalla, Louisiana State University, USA
Many efforts in Grid communities have focused on middleware research and development. However, Grid application-level tools are needed which can build higherlevel functionality on top of core middleware services. We work with specific classes of scientific applications and present a Grid-aware toolkit ResGrid for reservoir uncertainty analysis. With the help of the ResGrid, a reservoir engineer can transparently take advantage of Grid resources and services for compute-intensive and dataintensive uncertainty analysis as well as enforce the understanding of reservoir modeling. In this paper, the ResGrid is introduced in terms of overview, architecture, and implementation status.
Citation:
Zhou Lei, Dayong Huang, Archit Kulshrestha, Santiago Pena, Gabrielle Allen, Xin Li, Christopher White, Richard Duff, John R. Smith, Subhash Kalla, "ResGrid: A Grid-aware Toolkit for Reservoir Uncertainty Analysis," ccgrid, pp.249-252, Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06), 2006
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