40 research outputs found

    Incorporating Physical Information into Clustering for FPGAs

    Get PDF
    The traditional approach to FPGA clustering and CLB-level placement has been shown to yield significantly worse overall placement quality than approaches which allow BLEs to move during placement. In practice, however, modern FPGA architectures require computationally-expensive Design Rule Checks (DRC) which render BLE-level placement impractical. This thesis research addresses this problem by proposing a novel clustering framework that produces better initial clusters that help to reduce the dependence on BLE-level placement. The work described in this dissertation includes: (1) a comparison of various clustering algorithms used for FPGAs, (2) the introduction of a novel hybridized clustering framework for timing-driven FPGA clustering, (3) the addition of physical information to make better clusters, (4) a comparison of the implemented approaches to known clustering tools, and (5) the implementation and evaluation of cluster improvement heuristics. The proposed techniques are quantified across accepted benchmarks and show that the implemented DPack produces results with 16% less wire length, 19% smaller minimum channel widths, and 8% less critical delay, on average, than known academic tools. The hybridized approach, HDPack, is found to achieve 21% less wire length, 24% smaller minimum channel widths, and 6% less critical delay, on average

    High-Performance Placement and Routing for the Nanometer Scale.

    Full text link
    Modern semiconductor manufacturing facilitates single-chip electronic systems that only five years ago required ten to twenty chips. Naturally, design complexity has grown within this period. In contrast to this growth, it is becoming common in the industry to limit design team size which places a heavier burden on design automation tools. Our work identifies new objectives, constraints and concerns in the physical design of systems-on-chip, and develops new computational techniques to address them. In addition to faster and more relevant design optimizations, we demonstrate that traditional design flows based on ``separation of concerns'' produce unnecessarily suboptimal layouts. We develop new integrated optimizations that streamline traditional chains of loosely-linked design tools. In particular, we bridge the gap between mixed-size placement and routing by updating the objective of global and detail placement to a more accurate estimate of routed wirelength. To this we add sophisticated whitespace allocation, and the combination provides increased routability, faster routing, shorter routed wirelength, and the best via counts of published techniques. To further improve post-routing design metrics, we present new global routing techniques based on Discrete Lagrange Multipliers (DLM) which produce the best routed wirelength results on recent benchmarks. Our work culminates in the integration of our routing techniques within an incremental placement flow to improve detailed routing solutions, shrink die sizes and reduce total chip cost. Not only do our techniques improve the quality and cost of designs, but also simplify design automation software implementation in many cases. Ultimately, we reduce the time needed for design closure through improved tool fidelity and the use of our incremental techniques for placement and routing.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64639/1/royj_1.pd

    Timing-Driven Macro Placement

    Get PDF
    Placement is an important step in the process of finding physical layouts for electronic computer chips. The basic task during placement is to arrange the building blocks of the chip, the circuits, disjointly within a given chip area. Furthermore, such positions should result in short circuit interconnections which can be routed easily and which ensure all signals arrive in time. This dissertation mostly focuses on macros, the largest circuits on a chip. In order to optimize timing characteristics during macro placement, we propose a new optimistic timing model based on geometric distance constraints. This model can be computed and evaluated efficiently in order to predict timing traits accurately in practice. Packing rectangles disjointly remains strongly NP-hard under slack maximization in our timing model. Despite of this we develop an exact, linear time algorithm for special cases. The proposed timing model is incorporated into BonnMacro, the macro placement component of the BonnTools physical design optimization suite developed at the Research Institute for Discrete Mathematics. Using efficient formulations as mixed-integer programs we can legalize macros locally while optimizing timing. This results in the first timing-aware macro placement tool. In addition, we provide multiple enhancements for the partitioning-based standard circuit placement algorithm BonnPlace. We find a model of partitioning as minimum-cost flow problem that is provably as small as possible using which we can avoid running time intensive instances. Moreover we propose the new global placement flow Self-Stabilizing BonnPlace. This approach combines BonnPlace with a force-directed placement framework. It provides the flexibility to optimize the two involved objectives, routability and timing, directly during placement. The performance of our placement tools is confirmed on a large variety of academic benchmarks as well as real-world designs provided by our industrial partner IBM. We reduce running time of partitioning significantly and demonstrate that Self-Stabilizing BonnPlace finds easily routable placements for challenging designs – even when simultaneously optimizing timing objectives. BonnMacro and Self-Stabilizing BonnPlace can be combined to the first timing-driven mixed-size placement flow. This combination often finds placements with competitive timing traits and even outperforms solutions that have been determined manually by experienced designers

    New FPGA design tools and architectures

    Get PDF
    corecore