In typical integrated circuits (IC) designs, the final layout generally contains a lot of repeated patterns. Many of these repetitions are captured by the layout hierarchy. That is, the layout contains many cells that are each repeatedly placed in many locations with different transformation. Effective use of such repetition information in the computation intensive operations such as model-based optical proximity correction (OPC), verification, or contour generation, can lead to significant performance improvement. However, in many other occasions, such repetition information is not directly available. For example, if the layout is flattened, then all the hierarchy that captures the repetition information is lost. Even in hierarchical layout, a cell can contain repeated geometries or patterns. In order for the application to take advantage of such property, a mechanism to efficiently capture such repetition information is necessary. In this paper, we consider the model-based applications that have a unique property, which allows us to find different geometrical patterns that are equivalent in principle for simulation purpose. We introduce a proximity-based pattern identification method which aims at recognizing the maximum amount of repetition in the layout. This method not only captures repeated or symmetric geometries that are present from either the flattening of the hierarchy or within a cell itself, but also finds symmetries within the geometries themselves. The method also finds partial repetitions of geometries that are not completely identical or symmetric. Ideally, these “equivalent” patterns will eventually carry the same processing results with miniscule variations small enough to be ignored for the application. For this reason, it is sufficient to run the computationally expensive model-based operations for one of the pattern and carry the result to the rest of the patterns of the same family. Doing so reduces the problem size as well as the amount of data that requires processing. The total processing time therefore can be dramatically reduced. We demonstrate the method by using OPC as a test example. We show the level of problem size reduction and job run time reduction due to the specific nature of different layouts.