候选OBDD变量排序的快速函数评估

D. Ross, K. Butler, R. Kapur, M. R. Mercer
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引用次数: 37

摘要

通过有序二进制决策图(obdd)进行的符号仿真每年都变得越来越可行。在所表示的函数的变量的适当顺序下,这些表示通常是非常有效的。最近,对变量排序的启发式方法得到了发展,但由于启发式的性质,没有单一的启发式方法总是产生适当的排序。作者开发并分析了一种从几个候选排序中选择最佳排序的技术。排序选择方法速度快。将其排序与ISCAS85组合基准电路中功能(OBDD)计算期间排序的实际性能进行比较。与任何先前发布的单排序启发式方法相比,该方法允许在所有六个被调查的电路中使用更少的累积内存进行OBDD计算,并且在每个被检查的启发式方法中,也为这些电路中的一个或多个产生超过数量级的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast functional evaluation of candidate OBDD variable orderings
Symbolic simulation via ordered binary decision diagrams (OBDDs) is becoming more feasible each year. These representations are often very efficient under an appropriate ordering of the variables of the functions represented. Recently, heuristics for ordering variables have been developed, but due to the nature of heuristics, no single heuristic always produces an appropriate ordering. The authors develop and analyze a technique for selecting the best of several candidate orderings. The ordering selection method is fast. Its ranking of an ordering is compared to the actual performance of an ordering during functionals (OBDD) calculations in circuits from the ISCAS85 combinational benchmarks. Compared to any previously published single ordering heuristic, the method allows OBDD calculations using less cumulative memory over all six circuits investigated, and also produces over an order of magnitude improvement for one or more of these circuits, over every single heuristic examined.<>
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