TY - GEN

T1 - Machine-learning-based circuit synthesis

AU - Rokach, Lior

AU - Feldman, Alexander

AU - Kalech, Meir

AU - Provan, Gregory

PY - 2012

Y1 - 2012

N2 - Multi-level logic synthesis is a problem of immense practical significance, and is a key to developing circuits that optimize a number of parameters, such as depth, energy dissipation, reliability, etc. The problem can be defined as the task of taking a collection of components from which one wants to synthesize a circuit that optimizes a particular objective function. This problem is computationally hard, and there are very few automated approaches for its solution. To solve this problem we propose an algorithm, called Circuit-Decomposition Engine (CDE), that is based on learning decision trees, and uses a greedy approach for function learning. We empirically demonstrate that CDE, when given a library of different component types, can learn the function of Disjunctive Normal Form (DNF) Boolean representations and synthesize circuit structure using the input library. We compare the structure of the synthesized circuits with that of well-known circuits using a range of circuit similarity metrics.

AB - Multi-level logic synthesis is a problem of immense practical significance, and is a key to developing circuits that optimize a number of parameters, such as depth, energy dissipation, reliability, etc. The problem can be defined as the task of taking a collection of components from which one wants to synthesize a circuit that optimizes a particular objective function. This problem is computationally hard, and there are very few automated approaches for its solution. To solve this problem we propose an algorithm, called Circuit-Decomposition Engine (CDE), that is based on learning decision trees, and uses a greedy approach for function learning. We empirically demonstrate that CDE, when given a library of different component types, can learn the function of Disjunctive Normal Form (DNF) Boolean representations and synthesize circuit structure using the input library. We compare the structure of the synthesized circuits with that of well-known circuits using a range of circuit similarity metrics.

UR - http://www.scopus.com/inward/record.url?scp=84871953703&partnerID=8YFLogxK

U2 - 10.1109/eeei.2012.6377134

DO - 10.1109/eeei.2012.6377134

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AN - SCOPUS:84871953703

SN - 9781467346801

T3 - 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012

BT - 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012

T2 - 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012

Y2 - 14 November 2012 through 17 November 2012

ER -