A neural network approach to the placement problem

M. S. Zamani, G. Hellestrand
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引用次数: 3

Abstract

In this paper, we introduce a new neural network approach to the placement of gate array designs. The network used is a Kohonen self-organising map. An abstract specification of the design is converted to a set of appropriate input vectors fed to the network at random. At the end of the process, the map shows a 2-dimensional plane of the design in which the modules with higher connectivity are placed adjacent to each other, hence minimising total connection length in the design. The approach can consider external connections and is able to place modules in a rectilinear boundary. These features makes the approach capable of being used in hierarchical floorplanning algorithms.
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定位问题的一种神经网络方法
在本文中,我们引入了一种新的神经网络方法来放置门阵列设计。使用的网络是Kohonen自组织图。设计的抽象规范被转换成一组适当的输入向量,随机馈送到网络中。在流程结束时,地图显示了设计的二维平面,其中连接性较高的模块彼此相邻放置,从而最小化设计中的总连接长度。该方法可以考虑外部连接,并能够将模块放置在直线边界中。这些特点使该方法能够用于分层平面规划算法。
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