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The purpose of this paper is to detail a high-level analytical modelling and optimisation environment for mixed-granularity Field Programmable Gate Arrays (FPGAs). The work carried out for the purposes of this study involves the creation of an analytical framework that can be used to optimise the design of a reconfigurable device for a set of benchmarks. The strengths of this approach are the simultaneous placement, module selection and architecture generation. In this paper, the problem is cast as a formal optimisation, and may be solved using existing optimisation tools. In addition, the approach is adapted into an heuristic for larger benchmark sets. The design space is explored by examining the tradeoffs between area, speed and flexibility, and some comparisons to commercial architectures are drawn.

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Abstract-This paper is concerned with the application of formal optimisation methods to the design of mixed-granularity FPGAs. In particular, we investigate the appropriate mix and floorplan of heterogeneous elements: multipliers, RAMs, and LUT-based logic, in order to maximise the performance of a set of DSP benchmark applications, given a fixed silicon budget. A mathematical programming framework is introduced, along with a set of heuristics, capable of providing upper-bounds on the achievable reconfigurable-to-fixed-logic performance ratio. Moreover, we use linear-programming bounding procedures from the operations research community to provide lower-bounds on the same quantity. Our results provide, for the first time, quantifications of the optimal performance/area-enhancing capability of multipliers and RAM blocks within a system context. The approach detailed provides a formal mechanism to explore future technology nodes.