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研究生: 邱彥傑
Chiu, Yen-Chieh
論文名稱: 多層障礙物排除之直角史坦那樹之建置
On Constructing Multi-Layer Obstacle-Avoiding Rectilinear Steiner Trees
指導教授: 王廷基
Wang, Ting-Ghi
口試委員: 李毅郎
江蕙如
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Computer Science
論文出版年: 2011
畢業學年度: 100
語文別: 英文
論文頁數: 37
中文關鍵詞: 演算法繞線實體設計史坦那樹障礙物多層
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  • 在超大型積體電路設計中,一個直角史坦那樹常被用來作為網路內訊號的連接。在現在的設計內通常都含有許多直角的障礙物,像是動力網路系統、區塊型模組、矽智財模組及預先繞線好的網路,因此,建造一個排除礙障物的直角史坦那樹是一個重要的繞線問題。此外,現今的奈米製程設計提供了多層金屬層作為繞線環境;同時,金屬層上的特定方向條件也限制了每一層的繞線方向。因此,有人提出了「考慮障礙物的特定方向史坦那樹」的議題來應對這些實際的問題。在這篇碩士論文中,我們針對此議題提出了一個新穎、穩健及高品質的演算法。我們的演算法的概念是藉由一個直角史坦那樹的指引,企圖找到一些合適的史坦那頂點。我們也提供了多種最短路徑搜尋演算法來連接這些史坦那頂點和與其相鄰之頂點。此外,我們的方法也可以延伸處理「多層障礙物排除之直角史坦那樹」的問題;這是個排除特定方向條件的問題。實驗數據顯示,我們的演算法在處理「考慮障礙物的特定方向史坦那樹」和「多層障礙物排除之直角史坦那樹」的問題上,都可以得到很好的結果。


    In very large scale integration (VLSI) design, a rectilinear Steiner tree (RST) is usually
    used to guide router to connect signals for a net. However, In current technology, there
    are more and more rectilinear obstacles, such as power networks, macro cells, IP blocks
    and pre-routed nets. Therefore, a concept of obstacle-avoiding rectilinear Steiner minimal
    tree (OARSMT) has been noticed that can be applied on the routing problem. Besides, in
    modern nano-technology designs, there are multiple metal layers can be used for routing,
    at the same time, the preferred directions constraint limits the orientations of routing
    in each layer for the signal integrity consideration. As a result, the obstacle-avoiding
    preferred direction Steiner tree (OAPDST) problem has been proposed to cop with these
    practical problems. In this thesis, we present a novel, robust, and high quality OAPDST
    construction algorithm for this problem. Our algorithm is based on nding suitable Steiner
    points on a graph, and guided by an RST. Several shortest path nding algorithms were
    also proposed to connect every Steiner points and their neighbors with minimal wirelength.
    Besides, our approach can be easily extended to deal with multi-layer obstacle-avoiding
    rectilinear Steiner minimal tree (ML-OARSMT) problem. The experimental results show
    our algorithm performs well in total cost, both on OAPDST and ML-OARSMT problems.

    1 Introduction 2 2 Assumptions and Problem Formulation 7 2.1 Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3 Our Approach 9 3.1 Overview of Our Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.2 Step 1. Constructing an RST . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.3 Step 2. Determining the Positions of Steiner Points . . . . . . . . . . . . . 11 3.4 Step 3. Rip-up and Reroute Re nement . . . . . . . . . . . . . . . . . . . 20 3.5 Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4 Experimental Results 25 4.1 Results for the OAPDST Problem . . . . . . . . . . . . . . . . . . . . . . . 25 4.2 Results for the ML-OARSMT Problem . . . . . . . . . . . . . . . . . . . . 26 5 Conclusions 34

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