VASE: the visualization and application steering environment
Proceedings of the 1993 ACM/IEEE conference on Supercomputing
A tool framework for static and dynamic analysis of object-oriented software with templates
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
An Integrated Problem Solving Environment: The SCIRun Computational Steering System
HICSS '98 Proceedings of the Thirty-First Annual Hawaii International Conference on System Sciences-Volume 7 - Volume 7
Efficient Coupling of Parallel Applications Using PAWS
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
WPC '97 Proceedings of the 5th International Workshop on Program Comprehension (WPC '97)
The Architecture of the Earth System Modeling Framework
Computing in Science and Engineering
GCF: a general coupling framework
Concurrency and Computation: Practice & Experience - Computational Frameworks
PALM: a dynamic parallel coupler
VECPAR'02 Proceedings of the 5th international conference on High performance computing for computational science
A domain-specific language for model coupling
Proceedings of the 38th conference on Winter simulation
The role of composition and aggregation in modeling macromolecular regulatory networks
Proceedings of the 38th conference on Winter simulation
Fusing and composing macromolecular regulatory network models
SpringSim '07 Proceedings of the 2007 spring simulation multiconference - Volume 2
Model Composition for Macromolecular Regulatory Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Model coupling is a nontrivial task that is not adequately supported in existing frameworks. Our long term goal is to support the fast-prototyping of model couplings, enabling scientists to quickly experiment with a variety of linkings without having to make an upfront investment in reprogramming. This paper introduces the centerpiece of our framework, the Potential Coupling Interface (PCI), a visual representation of a model code based on simplified control flow graphs. The PCI serves three roles: it is a new form of metadata describing the coupling potential of a model; it is the vehicle for the specification of couplings; and it is the basis for automatic code generation. It is easy to specify and once specified, it is available for all future coupling activities. The PCI allows scientists to focus on the important domain and model issues of coupling without having to revisit legacy code for each new effort.