Architecture

The goal of the CME project is to develop an integrated environment in which a broad user community encompassing geoscientists, civil and structural engineers, educators, city planners, and disaster response teams can have access to powerful physics-based simulation techniques for seismic hazard analysis. To achieve this goal, the environment must provide a means for describing, configuring, instantiating, and executing complex computational pathways that result from the composition of various earthquake simulation models.

The proposed architecture of the CME is illustrated above. Click on the diagram to learn more about a given aspect of this architecture. The CME architecture brings together research from several distinct computer science disciplines (with each area addressing one of the project's four requirements):

1. Knowledge representation and reasoning techniques to manage the heterogeneity of the models and capture the complex relationships between the physical processes and the model algorithms, between the algorithms and the simulation codes, and between the simulation codes and the data products. Knowledge-based inference will be used to apply these representations to the problems of pathway construction, constraint checking, execution planning, and information access.
2. Grid technologies to enable access to distributed simulation codes and resources for the timely execution of the simulation scenarios defined by users, specifically by integrating high-performance computing resources into the execution environment available to the modeling framework. By providing mechanisms for the discovery, access, and management of distributed computation and storage resources, Grids address the distributed nature of the developers, resources and user environments.
3. Digital library technology to manage the collections of data and simulation code repositories and handle multiple versions of the models. Knowledge-based data management tools will provide an infrastructure for mediating access to existing seismic data catalogs and information repositories, as well as incorporating new collections of data generated by the simulations.
4. Interactive knowledge acquisition techniques to enable users with a range of sophistication to configure computational pathways. Knowledge acquisition tools support this activity by selecting appropriate simulation software and input data files from the code and information repositories available. These tools hide implementation details and present users with structured dialogues that guide them to provide information required to set up each simulation while resolving the constraints among the simulation models and their inputs.

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