基于遗传算法的VLSI平面规划复杂三角消除问题研究

R. Mishra, B. Sahana, Sukes Maiti, S. Samaddar
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摘要

本文提出了一种基于遗传算法(GA)的方案来解决超大规模集成电路(VLSI)平面规划中矩形二值化法的复杂三角形消去问题。矩形二值化是VLSI平面规划的重要方法,其中每个模块都被实现为一个矩形区域。已知,如果输入邻接图中包含一个复三角形(CT),即一个由三条边组成的循环,它不是一个面,那么它的矩形对偶不存在。因此,在构建平面图之前,消除ct变得至关重要。CTE问题有两个版本——加权邻接图和未加权邻接图。已知加权CTE问题是np完全的(Sun, 1993)。最近又证明了未加权问题也是np完全问题。本文提出了一种求解非加权CTE问题和加权CTE问题的遗传算法方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Investigation of Complex Triangle Elimination Problem of VLSI Floor Planning Employing Genetic Algorithmic Scheme
This paper provides a scheme based on genetic algorithm (GA) to solve the complex triangle elimination (CTE) problem of rectangular dualization approach in VLSI floor planning. Rectangular dualization, where each module is realized as a rectangular area, is an important approach in VLSI floor planning. It is known that if the input adjacency graph contains a complex triangle (CT), i.e. a cycle of three edges that is not a face, and then its rectangular dual does not exists. Elimination of CTs therefore becomes essential before constructing a floor plan. There are two versions of the CTE problems -weighted and unweighted adjacency graphs. The weighted CTE problem is known to be NP-complete (Sun, 1993). Recently it has been proved that unweighted problem is also NP-complete. In this paper we present a genetic algorithmic scheme to solve unweighted CTE problem and weighted CTE problem.
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