基于ROBDD的电路功耗估算方法

Circuit Power Consumption Estimation Method Based on ROBDD

概率功耗估算方法和条件概率功耗估算方法估算的功耗作为优化的成本函数时,由于方法本身的局限性或忽略了电路节点特点会降低估算结果的准确度,从而影响功耗优化结果。针对上述问题,提出一种新的电路功耗估算方法。该方法采用信号概率和跳变密度,并根据约简的有序二叉决策图(ROBDD)表示逻辑函数的特点,对ROBDD节点特征分类,从而对电路进行功耗估算。实验结果表明,该方法能够较好地预测电路的功耗,且功耗估算的精度优于概率估算方法和条件概率估算方法。

When the power consumption estimated by the probability power estimation method is used as the cost function for power optimization, the limitations of the methods themselves or ignoring the characteristics of the circuit node lead to lower accuracy of the estimation results and then affect the power optimization results. Aiming at these problems,a new power estimation method is proposed. It estimates the power effectively by giving the signal probability and transition density of input signals, and then classifying the characteristics of Reduced Ordered Binary Decision Diagram （ROBDD） nodes based on ROBDD representation. Experimental results show that this method can better predict the power consumption of the circuit, and the power consumption estimation precision is superior to that of the probability and conditional probability estimation methods.