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研究生: 林貴彥
Guei-yan Lin
論文名稱: 可閃避直角障礙物的直角擴張森林之建立改進
Revised obstacle-avoiding rectilinear spanning forest with rectilinear obstacles
指導教授: 項天瑞
Tien-Ruey Hsiang
口試委員: 鄧惟中
Wei-Chung Teng
羅乃維
none
學位類別: 碩士
Master
系所名稱: 電資學院 - 資訊工程系
Department of Computer Science and Information Engineering
論文出版年: 2012
畢業學年度: 100
語文別: 英文
論文頁數: 47
中文關鍵詞: 史坦納樹擴張樹路徑規劃
外文關鍵詞: Physical design, sapnning tree
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  • 繞線問題是超大型積體電路實體設計中非常重要的一部分,隨著半導體製程
    不斷的進步,晶片電路複雜度也與日俱增,單位面積的繞線密度也隨之大幅提
    升,繞線問題佔整體晶片設計效能的比例也提高了許多。然而,在現今積體電路
    設計中,有越來越多的障礙物,這些障礙物主要是智財區塊(IP block)、動力網路
    系統(power network)、已繞的繞線等,所以如何有效的決定繞線路徑來解決繞線
    問題,是一個相當重要的研究議題。

    我們考量一個給定的平面上存在著節點以及可重疊的直角障礙物,透過直線
    以及橫線且可能經過額外的史坦納點的集合,連結所有的節點並避免穿越任何障
    礙物,在可重疊的直角障礙物下,會產生個多個閉區間,使得最小線長的直角史
    坦納樹會有多棵,最後建構出具有最小線長的直角史坦納森林。

    在本篇論文中,我們提出一個新的避開重疊障礙物直角擴張森林建構的演算
    法,此方法較以往相關的文獻,能進行更有效率的平面掃描,快速的建立避開障
    礙物生成圖的時間。經由實際的模擬,我們的演算法能夠很可觀的減少障礙物生
    成時間,且能夠處理重疊障礙物的情況。


    In VLSI physical design, routing problem is an extremely important subject.
    As the semiconductor technologies progress, the complexity of chip circuit increases
    substantially. Thus, how to increase the efficiency in a physical circuit devise becomes
    an important research subject.

    Given a set of pins and a set of obstacles which can overlap each other on a
    plane, an obstacle-avoiding rectilinear Steiner minimal forest (OARSMF) connects
    these pins on each connected component, possibly through some additional points
    (called Steiner points), and avoids running through any obstacle to construct a forest
    with a minimal total wire-length.

    In this paper, we propose an obstacle-avoiding rectilinear Steiner forest (OARSF)
    construction algorithm. This method sweeps the plane more efficiently and constructs
    obstacle-avoiding rectilinear graph (OASG)fast. In our work, the experimental
    result shows our algorithm can reduce significant time to construct OASG
    and deal with overlapping obstacles.

    Table of Contents List of Tables List of Figures 1 Introduction 2 Related Work 3 The Proposed Approach 3.1 Problem Formulation 3.2 Our Algorithm 3.3 Data Preprocess 3.4 OASG Construction 3.5 OASF Construction 3.6 OARSF Construction 4 Performance Evaluation 5 Conclusions and Future Work Bibliography

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