Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present an analytic performance model of a large-scale hydrodynamics code developed at Los Alamos National Laboratory. This modeling work is part of an ongoing effort to develop models and modeling techniques for large-scale codes and systems of interest to Los Alamos and the national laboratory community (Kerbyson et al., 2001). Krak (Burton, 1994) comprises over 270,000 lines of source code and is capable of executing on a large number of parallel processors. Developing an accurate model is complicated by the irregular partitioning of input spatial grid cells to processors and the various material properties assigned to each cell. Model development proceeds by separating inter-processor communication from computation and modeling each individually. In addition, several approximations concerning subgrid size, shape, and material composition are made which reduce modeling complexity without adversely impacting prediction accuracy.  validate our model on several spatial grid sizes and processor configurations and demonstrate an accuracy at the largest scale on 512 processors to within a 3% error
['Kevin J. Barker', 'Scott Pakin', 'Darren J. Kerbyson']
I am writing a research paper on a idea A Performance Model of the Krak Hydrodynamics Application
[{"from": "human", "value": "I am writing a research paper on a idea A Performance Model of the Krak Hydrodynamics Application"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present an analytic performance model of a large-scale hydrodynamics code developed at Los Alamos National Laboratory. This modeling work is part of an ongoing effort to develop models and modeling techniques for large-scale codes and systems of interest to Los Alamos and the national laboratory community (Kerbyson et al., 2001). Krak (Burton, 1994) comprises over 270,000 lines of source code and is capable of executing on a large number of parallel processors. Developing an accurate model is complicated by the irregular partitioning of input spatial grid cells to processors and the various material properties assigned to each cell. Model development proceeds by separating inter-processor communication from computation and modeling each individually. In addition, several approximations concerning subgrid size, shape, and material composition are made which reduce modeling complexity without adversely impacting prediction accuracy.  validate our model on several spatial grid sizes and processor configurations and demonstrate an accuracy at the largest scale on 512 processors to within a 3% error"}]