Multiple objective optimisation in a behavioural synthesis system

The authors describe the implementation of an `intelligent´ silicon compiler that provides the ability to optimise a design, given as a behavioural description, with respect to multiple objectives. The user submits goals or objectives to the system, named MOODS, which automatically finds an optimal solution in the context of the user-specified constraints. The MOODS system provides a sound basis for multiple objective optimisation and allows the user to characterise and explore the design space. An accurate representation of the implementations in the design space is ensured by feeding up technology-dependent information from a cell library. This data is used in a global cost function which guides the application of transformations on a multilevel representation of the design. The results obtained show that designs can be produced which meet users´ objectives and that a varied set of implementations can be synthesised from a single behavioural specification. The resulting characteristics of the set of implementations enable the design space to be characterised