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DAGaware AIG rewriting: A fresh look at combinational logic synthesis
 In DAC ’06: Proceedings of the 43rd annual conference on Design automation
, 2006
"... This paper presents a technique for preprocessing combinational logic before technology mapping. The technique is based on the representation of combinational logic using AndInverter Graphs (AIGs), the networks of twoinput ANDs and inverters. The optimization works by alternating DAGaware AIG rew ..."
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Cited by 76 (32 self)
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This paper presents a technique for preprocessing combinational logic before technology mapping. The technique is based on the representation of combinational logic using AndInverter Graphs (AIGs), the networks of twoinput ANDs and inverters. The optimization works by alternating DAGaware AIG rewriting, which reduces area by sharing common logic without increasing delay, and algebraic AIG balancing, which minimizes delay without increasing area. The new technologyindependent flow is implemented in a publicdomain tool ABC. Experiments on large industrial benchmarks show that the proposed methodology scales to very large designs and is several orders of magnitude faster than SIS and MVSIS while offering comparable or better quality when measured by the quality of the network after mapping. 1
An introduction to zerosuppressed binary decision diagrams
 in ‘Proceedings of the 12th Symposium on the Integration of Symbolic Computation and Mechanized Reasoning
, 2001
"... ..."
Semantic Minimization of 3Valued Propositional Formulae
 In Proc. Symp. on Logic in Comp. Sci
, 2002
"... This paper presents an algorithm for a nonstandard logicminimization problem that arises in 3valued propositional logic. The problem is motivated by the potential for obtaining better answers in applications that use 3valued logic. An answer of 0 or 1 provides precise (definite) information; an a ..."
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Cited by 7 (3 self)
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This paper presents an algorithm for a nonstandard logicminimization problem that arises in 3valued propositional logic. The problem is motivated by the potential for obtaining better answers in applications that use 3valued logic. An answer of 0 or 1 provides precise (definite) information; an answer of 1=2 provides imprecise (indefinite) information. By replacing a formula ' with a "better" formula , we may improve the precision of the answers obtained. In this paper, we give an algorithm that always produces a formula that is "best" (in a certain welldefined sense).
Exploring multivalued minimization using binary methods
 in International Workshop on Logic and Synthesis
, 2003
"... A transformation of multivalued input binaryoutput functions, called cosingleton transform (CST), was introduced in [11] to reduce algebraic multivalued (MV) operations to binary. In this paper, we explore its potential for a number of problems related to MV SOP minimization, such as computing I ..."
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Cited by 1 (1 self)
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A transformation of multivalued input binaryoutput functions, called cosingleton transform (CST), was introduced in [11] to reduce algebraic multivalued (MV) operations to binary. In this paper, we explore its potential for a number of problems related to MV SOP minimization, such as computing ISOPs, the set of all primes, and the set of all essential primes. Experimental results show that in some cases these problems can be solved more efficiently than by the traditional MV SOP minimization approaches represented by ESPRESSOMV, but that generally there is no clear methodofchoice. 1
A Symbolic Algorithm for Low Power Sequential Synthesis
 In Int’l Symp. on Low Power Electronics and Design
, 1997
"... We present an algorithm that restructures the state transition graph (STG) of a sequential circuit so as to reduce power dissipation. The STG is modified without changing the behavior of the circuit, by exploiting state equivalence. Rather than aiming primarily at reducing the number of states, our ..."
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Cited by 1 (0 self)
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We present an algorithm that restructures the state transition graph (STG) of a sequential circuit so as to reduce power dissipation. The STG is modified without changing the behavior of the circuit, by exploiting state equivalence. Rather than aiming primarily at reducing the number of states, our algorithm redirects transitions so that the new destination states are equivalent to the original ones, while the average activity of the circuit is decreased. The impact on area is also estimated to increase the accuracy of the power analysis. The STG and all other major data structures are stored as decision diagrams, and the algorithm does not enumerate explicitly the states or the transitions. (i.e., it is symbolic.) Therefore, it can deal with circuits that have millions of states. Once the STG has been restructured we apply symbolic factoring algorithms, based on Zerosuppressed BDDs, to convert the optimized graph into a multilevel circuit. We derive an efficient circuit from the BDDs...
Binary Decision Diagrams and Applications for Reliability Analysis
, 2000
"... This thesis investigates practical and theoretical concerns for the use of Binary Decision Diagrams (BDDs) for qualitative and quantitative risk assessments of complex systems. Boolean models describing failure relationships between components, and fault trees in particular, are boolean formulas who ..."
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This thesis investigates practical and theoretical concerns for the use of Binary Decision Diagrams (BDDs) for qualitative and quantitative risk assessments of complex systems. Boolean models describing failure relationships between components, and fault trees in particular, are boolean formulas whose variables are individual component failures; assessment of these models can be performed by analysis of the boolean function induced by the formula. Resource consumption for BDD computations, which is determined by the form of the boolean formula and the order imposed on its variables, is in many cases exponentially smaller than the truth table for the function. The use of Binary Decision Diagrams has made possible ordersofmagnitude increases in the complexity of systems that can be assessed efficiently. Nonetheless, the practical limits of straightforward use of BDDs for reliability analysis are often surpassed by realworld systems. Understanding why this happens is the first subject...