In this paper, the glitching activity and process variations in the maximum power dissipation estimation of CMOS circuits are introduced. Given a circuit and the gate library, a new Genetic Algorithm (GA)-based techni...In this paper, the glitching activity and process variations in the maximum power dissipation estimation of CMOS circuits are introduced. Given a circuit and the gate library, a new Genetic Algorithm (GA)-based technique is developed to determine the maximum power dissipation from a statistical point of view. The simulation on 1SCAS-89 benchmarks shows that the ratio of the maximum power dissipation with glitching activity over the maximum power under zero-delay model ranges from 1.18 to 4.02. Compared with the traditional Monte Carlo-based technique, the new approach presented in this paper is more effective.展开更多
基金Supported by NSF of the United States under contract 5978 East Asia and Pacific Program 9602485
文摘In this paper, the glitching activity and process variations in the maximum power dissipation estimation of CMOS circuits are introduced. Given a circuit and the gate library, a new Genetic Algorithm (GA)-based technique is developed to determine the maximum power dissipation from a statistical point of view. The simulation on 1SCAS-89 benchmarks shows that the ratio of the maximum power dissipation with glitching activity over the maximum power under zero-delay model ranges from 1.18 to 4.02. Compared with the traditional Monte Carlo-based technique, the new approach presented in this paper is more effective.
