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A new and efficient congestion evaluation model in floorplanning: wire density control with twin binary trees

机译:布局规划中一种新的高效拥塞评估模型:双二叉树的线密度控制

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As technology moves into the deep-submicron era, the complexity of VLSI circuit design grows rapidly, especially in the interconnections between modules. Therefore, interconnect optimization has become an important concern in floorplanning today. Most routability-driven floorplanners use a grid-based approach that divides a floorplan into grids as in global routing. Congestion is estimated as the expected number of nets passing through each grid. Although this approach is direct and accurate, it is not efficient when dealing with complex circuits containing thousands of nets. In this paper, an efficient and innovative routability-driven floorplanner, using a twin binary trees (TBT) representation is proposed. The congestion model we used is the wire density on the half-perimeter boundary of different regions in a floorplan. These regions are defined naturally by the TBT representation. In order to increase the efficiency of our floorplanner, a fast algorithm for the least common ancestor (LCA) problem is used to compute the wire density. From the experimental results, the number of unroutable wires can be reduced in a short time.
机译:随着技术进入深亚微米时代,VLSI电路设计的复杂性迅速增长,尤其是在模块之间的互连中。因此,互连优化已成为当今布局规划中的重要问题。大多数可布线性驱动的平面规划师使用基于网格的方法,如全局路由一样,将平面图分为多个网格。拥塞估计为通过每个网格的网的预期数量。尽管此方法是直接且准确的,但在处理包含数千个网络的复杂电路时效率不高。在本文中,提出了一种高效且具有创新性的可布线性驱动的平面规划器,它使用双二叉树(TBT)表示。我们使用的拥塞模型是平面图中不同区域的半周边界上的导线密度。这些区域由TBT表示法自然定义。为了提高我们的平面布置图的效率,使用了一种针对最小公共祖先(LCA)问题的快速算法来计算导线密度。根据实验结果,可以在短时间内减少不可布线的数量。

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