Flexible Two-Level Boolean Minimizer BOOM-II and Its Applications

Fišer, Petr; Kubátová, Hana

doi:10.1109/dsd.2006.53

Cited by 21 publications

(11 citation statements)

References 13 publications

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“…2.4 BOOM-II (from BOOlean Minimization) Fišer and Kubátová (2006) from the Czech Technical University continued the work on Espresso but under a different philosophy. Unlike all the other software that produce implicants bottom-up, this method applies a top-bottom strategy: while the classic QuineMcCluskey algorithm gradually reduces the number of literals from an initial expression, BOOM starts from the simplest possible expressions and it gradually adds literals until a minimum solution is found.…”

Section: Espressomentioning

confidence: 98%

A mathematical approach to the boolean minimization problem

Duşa

2008

Qual Quant

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Section: Espressomentioning

confidence: 98%

A mathematical approach to the boolean minimization problem

Duşa

2008

Qual Quant

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“…The second version of BOOM, BOOM-II [35], combines the initial algorithm with another one called FC-Min [36] in order to solve minimization problems with a large number of output variables. It is very fast for this purpose, the runtime grows almost linearly with growing number of both the input and output variables [36].…”

Section: Boom and Fc-minmentioning

confidence: 99%

“…However, the results this method produces does not reach the quality of other minimizers. Therefore, the developers of this method proposed its application as a pre-processor to other methods such as ESPRESSO to significantly reduce total minimization time, while fully retaining the result quality [35].…”

Section: Boom and Fc-minmentioning

confidence: 99%

Logic Synthesis as an Efficient Means of Minimal Model Discovery from Multivariable Medical Datasets

Gorji

Poon

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

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In this paper we review the application of logic synthesis methods for uncovering minimal structures in observational/medical datasets. Traditionally used in digital circuit design, logic synthesis has taken major strides in the past few decades and forms the foundation of some of the most powerful concepts in computer science and data mining. Here we provide a review of current state of research in application of logic synthesis methods for data analysis and provide a demonstrative example for systematic application and reasoning based on these methods.

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“…Scherzo [21], employing BDDs to represent prime implicants implicitly, allowed an exact minimization of rather difficult functions. Afterwards, a two-level Boolean minimizer Boom [10,11] has been developed.…”

Section: Introductionmentioning

confidence: 99%

A Fast SOP Minimizer for Logic Funcions Described by Many Product Terms

Fišer

Toman

2009

2009 12th Euromicro Conference on Digital System Design, Architectures, Methods and Tools

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We introduce a fast and efficient minimization method for functions described by many (up to millions) product terms. The algorithm is based on processing a newly proposed efficient representation of a set of product terms -a ternary tree. A significant speedup of the look-up of the term operation is achieved, with respect to a standard tabular function representation. The minimization procedure is based on a fast application of basic Boolean operations upon a ternary tree. Minimization of incompletely specified functions is supported as well. The minimization method was tested on randomly generated large sums-of-products and collapsed ISCAS benchmark circuits. The performance of the proposed algorithm was compared with Espresso. A very advantageous application of the new minimization algorithm has been found -if it is used for pre-processing a function having a large number of product terms, run prior to Espresso, the total minimization runtime is significantly reduced, whereas the result quality is not affected.

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Flexible Two-Level Boolean Minimizer BOOM-II and Its Applications

Cited by 21 publications

References 13 publications

A mathematical approach to the boolean minimization problem

A mathematical approach to the boolean minimization problem

Logic Synthesis as an Efficient Means of Minimal Model Discovery from Multivariable Medical Datasets

A Fast SOP Minimizer for Logic Funcions Described by Many Product Terms

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