TY - GEN
T1 - Machine-learning-based circuit synthesis
AU - Rokach, Lior
AU - Feldman, Alexander
AU - Kalech, Meir
AU - Provan, Gregory
PY - 2012/12/1
Y1 - 2012/12/1
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
M3 - Conference contribution
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 -