利用强对称性最小化不完全指定布尔函数的ROBDD大小

Proceedings European Design and Test Conference. ED & TC 97 Pub Date : 1997-03-17 DOI:10.1109/EDTC.1997.582364

Christoph Scholl, S. Melchior, G. Hotz, P. Molitor

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引用次数: 20

摘要

给出了一种计算不完全布尔函数的变量划分为对称群的最小大小的方法。该方法可用于不完全指定布尔函数的robdd的最小化。我们将其应用于Panda(1994)和Moller(1994)提出的对称筛选的预处理步骤，以及Chang(1994)和Shiple(1994)提出的不完全指定布尔函数的ROBDD最小化技术。该技术被证明是非常有效的:它将对称筛选的ROBDD尺寸提高了51%，并与Chang和Shiple技术的稍微修改版本相结合，提高了70%。

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Minimizing ROBDD sizes of incompletely specified Boolean functions by exploiting strong symmetries

We present a method computing a minimum sized partition of the variables of an incompletely specified Boolean function into symmetric groups. The method can be used during minimization of ROBDDs of incompletely specified Boolean functions. We apply it as a preprocessing step of symmetric sifting presented by Panda (1994) and Moller (1994) and of techniques for ROBDD minimization of incompletely specified Boolean functions presented by Chang (1994) and Shiple (1994). The technique is shown to be very effective: it improves ROBDD sizes of symmetric sifting by a factor of 51% and by a factor of 70% in combination with a slightly modified version of the technique of Chang and Shiple.

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Proceedings European Design and Test Conference. ED & TC 97

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