Hierarchical Modelling of Generators in Design-Space Exploration

Modern FPGA designs are often composed of multiple interacting components. In a design reuse methodology, selecting the best IP for each component as well as values for its parameters is a challenging task due to the time needed to evaluate each possible variant. Model-based approaches for searching the design space have proven to be effective for helping select the best design. However, they do not take advantage of hierarchical information available in the FPGA tool flow. In this work, we describe how to decompose a probabilistic model of a system into hierarchical components and use the model to improve the optimization speed for this design-space exploration problem.