Advancement of Environmental Decision Support Systems Through High Performance Computing CommunicationEPA Grant Number: R825196
Title: Advancement of Environmental Decision Support Systems Through High Performance Computing Communication
Investigators: Brill, E. Downey , Baugh, John W. , Fine, Steven S. , Loughlin, Daniel , Ranjithan, S. Ranji , Wheeler, Neil J.M.
Current Investigators: Brill, E. Downey , Baugh, John W. , Fine, Steven S. , Loughlin, Daniel , Ranjithan, S. Ranji
Institution: North Carolina State University , MCNC / North Carolina Supercomputing Center
Current Institution: North Carolina State University
EPA Project Officer: Hahn, Intaek
Project Period: October 1, 1996 through September 30, 1999 (Extended to September 30, 2000)
Project Amount: $599,932
RFA: High Performance Computing (1996) RFA Text | Recipients Lists
Research Category: Health , Ecosystems , Environmental Statistics
Description:The goal of the proposed research is to overcome the current computational resource limitations by developing tools for use within a high performance computing and communications (HPCC) environment, bringing DSSs closer to realizing the decision making power of a true joint-cognitive system. To meet this goal, there are four primary research objectives: 1) to explore further the role of various optimization techniques in a DSS framework for complex environmental problems, 2) to examine ways of making better use of existing and expected future computational power to increase performance, 3) to continue the development of better DSS prototypes, and 4) to evaluate each prototype's performance and user interface with respect to user needs.
The tasks to be undertaken to meet these objectives include: investigation and development of optimization approaches, creation of prototype DSSs using parallel and distributed computing, development of DSS prototypes to improve the DSS's interface functionality and user-DSS interaction, evaluation by potential users, and reporting of results and conclusions.
Upon completion of this research project, a series of incrementally improved DSSs will be built. The prototypes will make use of parallel machines and distributed networks to speed what-if and optimization analyses. Advancements in DSSs have the potential of benefiting many environmental fields, as well as very different disciplines. The results will constitute advances in applied optimization, decision support systems, environmental decision making, and parallel and distributed computing.