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New Width Inference Algorithm

New Width Inference Algorithm. Bert Rodiers Ben Lickly. Has 2 relations to be inferred connected to it. Old algorithm would fail. Rationale

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New Width Inference Algorithm

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  1. New Width Inference Algorithm Bert Rodiers Ben Lickly Has 2 relations to be inferred connected to it. Old algorithm would fail. • Rationale • In Ptolemy II relations can have multiple channels, each one representing a sequence of tokens. The number of channels is specified by the width of a relation. Having to explicitly specify the width for each relation can be a tedious job. To make it even worse, the addition of one relation to a multiport might result in a model builder needing to go through the model again to adapt widths. To cope with this you can let the relations infer the width from other relations or other ports with a graph algorithm. Constraints mechanism on ports • Restricted existing algorithm • Only one relation to be inferred at each port Width of relation connected to output, has to be equal to True and False input. output.setWidthEquals(trueInput); output.setWidthEquals(falseInput); Performance • Properties of new algorithm • Widths are propagated • Each relation is only visited once • Not all widths can be inferred • More expensive algorithm • Initialization step: O(total number of relations) Center for Hybrid and Embedded Software Systems

  2. A graph algorithm is often a trade-off between completeness of the algorithm and the complexity of the algorithm. There was already an existing fast implementation that had many limitations and hence we tried to come up with a solution that can infer the width for most scenarios without imposing a large performance cost. The algorithm propagates the widths it knows and at multiports tries to infer the widths of other relations from these propagated widths. However there are some cases that don't work. Models that fail

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