Search

Architecture and CAD are closely related issues in FPGA design. Routing architecture design shall optimize routability and facilitate router development; on the other hand, router design shall consider the specific properties of routing architectures to optimize the performance of the router. In this paper, we propose effective and efficient unified matching-based algorithms for array-based FPGA routing and segmentation design. For the segmentation design, we consider the similarity of input routing instances and formulate a net-matching problem to construct the optimal segmentation architecture. For the router design, we present a matching-based timing-driven routing algorithm which can consider a versatile set of routing segments. Experimental results show that our designed segmentations significantly outperform those used in commercially available FPGAs. For example, our designed segmentations achieve, on average, 14.6% and 19.7% improvements in routability, compared with those used in the Lucent Technologies ORCA 2C-series and the Xilinx XC4000E-series FPGAs, respectively.

We extend in this paper the concept of the P-admissible floorplan representation to that of the P*-admissible one. A P*-admissible representation can model the most general floorplans. Each of the currently existing P*-admissible representations, SP, BSG, and TCG, has its strengths as well as weaknesses. We show the equivalence of the two most promising P*-admissible representations, TCG and SP, and integrate TCG with a packing sequence (part of SP) into a new representation, called TCG-S. TCG-S combines the advantages of SP and TCG and at the same time eliminates their disadvantages. With the property of SP, faster packing and perturbation schemes are possible. Inherited nice properties from TCG, the geometric relations among modules are transparent to TCG-S (implying faster convergence to a desired solution), placement with position constraints becomes much easier, and incremental update for cost evaluation can be realized. These nice properties make TCG-S a superior representation which exhibits an elegant solution structure to facilitate the search for a desired floorplan/placement. Extensive experiments show that TCG-S results in the best area utilization, wirelength optimization, convergence speed, and stability among existing works and is very flexible in handling placement with special constraints.

In this paper, we propose a transitive closure graph-based representation for general floorplans, called TCG, and show its superior properties. TCG combines the advantages of popular representations such as sequence pair, BSG, and B*-tree. Like sequence pair and BSG, but unlike O-tree, B*-tree, and CBL, TCG is P-admissible. Like B*-tree, but unlike sequence pair, BSG, O-tree, and CBL, TCG does not need to construct additional constraint graphs for the cost evaluation during packing, implying faster runtime. Further, TCG supports incremental update during operations and keeps the information of boundary modules as well as the shapes and the relative positions of modules in the representation. More importantly, the geometric relation among modules is transparent not only to the TCG representation but also to its operations, facilitating the convergence to a desired solution. All these properties make TCG an effective and flexible representation for handling the general floorplan/placement design problems with various constraints. Experimental results show the promise of TCG.

Process technology advances will soon make the one-million gate FPGA a reality. A key issue that needs to be solved for the large-scale FPGAs to realize their full potential lies in the design of their segmentation architectures. One-dimensional segmentation designs have been studied to some degree in much of the literature; most of the previously proposed methods are based on stochastic or analytical analysis. In this paper, we address a new direction for studying segmentation architectures. Our method is based on graph-theoretic formulation. We first formulate a net matching problem and present a polynomial-time optimal algorithm to solve the problem. Based on the solution to the problem, we develop an effective and efficient matching-based algorithm for FPGA segmentation designs. Experimental results show that our method significantly outperforms previous work.