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A Comparison of Decision Tree Approach and Neural Networks Based Heuristic Dynamic Programming Approach for Subcircuit Extraction Problem

机译:基于决策树方法和基于神经网络的子狼子提取问题的启发式动态规划方法

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The applications of non-standard logic device are increasing fast in the industry. Many of these applications require high speed, low power, functionality and flexibility, which cannot be obtained by standard logic device. These special logic cells can be constructed by the topology design strategy automatically or manually. However, the need arises for the topology design verification. The layout versus schematic (LVS) analysis is an essential part of topology design verification, and subcircuit extraction is one of the operations in the LVS testing. In this paper, we first provided an efficient decision tree approach to the graph isomorphism problem, and then effectively applied it to the subcircuit extraction problem based on the solution to the graph isomorphism problem. To evaluate its performance, we compare it with the neural networks based heuristic dynamic programming algorithm (SubHDP) which is by far one of the fastest algorithms for subcircuit extraction problem.
机译:非标准逻辑器件的应用在行业中快速增加。许多这些应用需要高速,低功耗,功能和灵活性,不能通过标准逻辑设备获得。这些特殊的逻辑单元可以自动或手动地由拓扑设计策略构成。但是,需要为拓扑设计验证而产生。布局与原理图(LVS)分析是拓扑设计验证的重要组成部分,并且Subcircuit提取是LVS测试中的操作之一。在本文中,我们首先提供了一种有效的决策树方法来实现图中的相像问题,然后基于对图同构术问题的解决方案有效地将其应用于子类提取问题。为了评估其性能,我们将其与基于神经网络的启发式动态编程算法(SubHDP)进行比较,该算法是迄今为止驻使子狼局提取问题最快的算法之一。

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