A Fast Classification Method of Isomorphic Polygons in Design Data of Large Scale Integrated Circuit

S. Shoji, A. Koyama
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引用次数: 1

Abstract

A large number of isomorphic polygons are included in design data of large scale integrated circuit. Fast search and classification for isomorphic polygons in these design data are expected to apply to compactification of design data and fast pattern search. A pattern matching method was proposed to reduce a large amounts of design data efficiently. In this method, feature of polygon shape is expressed by an angle-segment sequence called contour signature. So, this method realizes fast processing by efficient comparison using the contour signature. Furthermore, this method realizes compactification of the design data by hashing of classification results. However, there is a problem that feature amounts increase with increase of the number of vertices of polygons. As a result, computation amounts and memory usage amounts are increased. To solve this problem, in this paper, we propose a high speed and high accuracy classification method of isomorphic polygons. The proposed method can reduce a shape comparison process significantly by using a geometric invariant feature value for a polygon. The feature value is calculated by summation of distance from each vertex to center of gravity, and a polygon contour length. This value does not be affected by parallel shift, rotation and reduced scale. The feature value is same for isomorphic polygons and it is possible to fast access an isomorphic polygon group. From evaluation results of the proposed method, we verified that the proposed method can realize fast classification for isomorphic polygons, and compactification of design data.
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大型集成电路设计数据中同构多边形的快速分类方法
大规模集成电路的设计数据中包含了大量的同构多边形。这些设计数据中同构多边形的快速搜索和分类有望应用于设计数据的紧化和快速模式搜索。为了有效地减少大量的设计数据,提出了一种模式匹配方法。该方法将多边形的形状特征用一种称为轮廓特征的角段序列来表示。因此,该方法利用轮廓特征进行有效比较,实现了快速处理。此外,该方法通过对分类结果进行哈希,实现了设计数据的紧致化。然而,存在一个问题,即随着多边形顶点数量的增加,特征数量也会增加。因此,计算量和内存使用量都会增加。为了解决这一问题,本文提出了一种高速、高精度的同构多边形分类方法。该方法利用多边形的几何不变特征值,大大减少了形状比较过程。特征值由每个顶点到重心的距离和多边形轮廓长度的总和计算得到。该值不受平行移动、旋转和缩小比例的影响。同构多边形的特征值是相同的,可以快速访问同构多边形群。通过对该方法的评价,验证了该方法能够实现同构多边形的快速分类和设计数据的紧化。
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