X. Guo, A. Stoica, R. Zebulum, and D. Keymeulen (USA)
Evolvable Hardware, Mixtrinsic Evolution,Reconfigurable Circuits.
This paper introduces a new approach to the development of equivalent models. Models of various accuracy and simulation speed may be needed in different contexts of design and analysis, or within different simulators. The models may be of similar or different nature, and could be for example structural or behavioral. Traditional model development and tuning is manual, and proceeds by finding one of the models, which is then used to derive equivalent model(s), e.g. a simpler behavioral model. It is not guarantied that this simpler equivalent model is consistent with the thing it models in the first place (although it may be an approximation of the more complex model). This paper offers a means to automate modeling and derive the two or more equivalent models simultaneously and consistent with each other. The approach presented here relies on search algorithms to automatically explore the space of possible solutions in different model search spaces, alternating the evaluation of models of different type and resulting in models that have consistent behavior. This mixed-model search (MMS) approach is demonstrated with an example in which an evolutionary algorithm used as the search method automatically determines consistent equivalent models for a problem in which a software model and a hardware model would be otherwise inconsistent.
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