Efficient mapping of mathematical expressions to FPGAs: Exploring different design methodologies

Computationally intensive problems can be represented with data-flow graphs and automatically transformed to locally controlled floating-point units via partitioning. In theory the lack of global control signals enables high performance implementation however placing and routing of the partitioned circuits are not trivial. In practice to create a high performance implementation the clusters should be placed efficiently on the surface of an FPGA using the physical constraining feature of CAD tools. In the paper a new partitioning strategy is presented which not only minimizes the number of cut nets but produce partition which can be mapped without long interconnections between the clusters. The new strategy is demonstrated during the automatic circuit generation from a complex mathematical expression. The proposed partitioning method produces more cut nets than common strategies however the resulting partition can be easily mapped and operate on significantly higher frequency.