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Efficient Computation of Canonical Form under Variable Permutation and Negation for Boolean Matching in Large Libraries

机译:大型库中布尔匹配的变量排列和否定下的规范形式的高效计算

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摘要

This paper presents an efficient technique for solving a Boolean matching problem in cell-library binding, where the number of cells in the library is large. As a basis of the Boolean matching, we use the notion NP-representative (NPR): two functions have the same NPR if one can be obtained from the other by a permutation and/or comple-mentation(s) of the variables. By using a table look-up and a tree-based breadth-first search strategy, our method quickly computes the NPR for a given function. Boolean matching of the given function against the whole library is determined by checking the presence of its NPR in a hash table, which stores NPRs for all the library functions and their complements. The effectiveness of our method is demonstrated through experimental results, which show that it is more than two orders of magnitude faster than the Hinsberger-Kolla's algorithm.
机译:本文提出了一种有效的技术,用于解决单元库中单元格数量较多的单元库绑定中的布尔匹配问题。作为布尔匹配的基础,我们使用概念 NP 代表 (NPR):如果一个函数可以通过变量的排列和/或完成从另一个函数获得,则两个函数具有相同的 NPR。通过使用表格查找和基于树的广度优先搜索策略,我们的方法可以快速计算给定函数的NPR。给定函数与整个库的布尔匹配是通过检查其 NPR 在哈希表中的存在来确定的,哈希表存储所有库函数及其补码的 NPR。实验结果证明了该方法的有效性,结果表明该方法比Hinsberger-Kolla算法快了两个数量级以上。

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