TY - JOUR
T1 - Area and power optimization approach for mixed polarity Reed–Muller logic circuits based on multi-strategy bacterial foraging algorithm
AU - Zhou, Yuhao
AU - He, Zhenxue
AU - Wang, Tao
AU - Huo, Zhisheng
AU - Xiao, Limin
AU - Wang, Xiang
N1 - Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/11
Y1 - 2022/11
N2 - Area and power optimization have become the primary constraints in chip design. Existing area and power optimization approaches have poor optimization performance and high CPU time in logic circuits with multiple inputs. To solve this problems, we propose a multi-strategy bacterial foraging algorithm (MBFA) for multi-objective optimization, which includes nondominated add procedure, dual-population cooperative procedure, high-quality replication procedure, distributed migration procedure and the termination criterion. In addition, considering the characteristics of mixed polarity Reed–Muller (MPRM) logic circuits such as high dimension and large solution space domain, we propose an area and power optimization approach (APOA) based on XNOR/OR, which uses MBFA to search MPRM circuits with Pareto optimal solutions. Experimental results show that the APOA has better performance in optimizing MPRM circuits area and power.
AB - Area and power optimization have become the primary constraints in chip design. Existing area and power optimization approaches have poor optimization performance and high CPU time in logic circuits with multiple inputs. To solve this problems, we propose a multi-strategy bacterial foraging algorithm (MBFA) for multi-objective optimization, which includes nondominated add procedure, dual-population cooperative procedure, high-quality replication procedure, distributed migration procedure and the termination criterion. In addition, considering the characteristics of mixed polarity Reed–Muller (MPRM) logic circuits such as high dimension and large solution space domain, we propose an area and power optimization approach (APOA) based on XNOR/OR, which uses MBFA to search MPRM circuits with Pareto optimal solutions. Experimental results show that the APOA has better performance in optimizing MPRM circuits area and power.
KW - Area and power optimization
KW - MPRM logic circuits
KW - Multi-objective optimization
KW - Multi-strategy bacterial foraging algorithm
KW - Pareto optimal solutions
UR - https://www.scopus.com/pages/publications/85140805989
U2 - 10.1016/j.asoc.2022.109720
DO - 10.1016/j.asoc.2022.109720
M3 - 文章
AN - SCOPUS:85140805989
SN - 1568-4946
VL - 130
JO - Applied Soft Computing
JF - Applied Soft Computing
M1 - 109720
ER -