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Efficient statistical approach to estimate power considering uncertain properties of primary inputs

机译:考虑主要输入的不确定属性的有效统计方法来估计功率

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Power dissipation in complementary metal-oxide-semiconductor (CMOS) circuits is heavily dependent on the signal properties of the primary inputs. Due to uncertainties in specification of such properties, the average power should be specified between a maximum and a minimum possible value. Due to the complex nature of the problem, it is practically impossible to use traditional power estimation techniques to determine such bounds. In this paper, we present a novel approach to accurately estimate the maximum and minimum bounds for average power using a technique which calculates the sensitivities of average power dissipation to uncertainties in specification of primary inputs. The sensitivities are calculated using a novel statistical technique and can be obtained as a by-product of average power estimation using Monte Carlo-based approaches. The signal properties are specified in terms of signal probability (probability of a signal being logic ONE) and signal activity (probability of signal switching). Results show that the maximum and minimum average power dissipation can vary widely if the primary input probabilities and activities are not specified accurately.
机译:互补金属氧化物半导体(CMOS)电路的功耗在很大程度上取决于主要输入的信号特性。由于此类属性的规格不确定,因此应在最大和最小可能值之间指定平均功率。由于问题的复杂性,实际上不可能使用传统的功率估算技术来确定此类界限。在本文中,我们提出了一种新颖的方法,可以使用一种技术来准确估计平均功率的最大和最小范围,该技术可以计算平均功率耗散对主输入规格不确定性的敏感性。灵敏度是使用新型统计技术计算得出的,可以使用基于蒙特卡洛的方法作为平均功率估算的副产品获得。根据信号概率(信号为逻辑“ 1”的概率)和信号活动(信号切换的概率)来指定信号属性。结果表明,如果未正确指定主要输入概率和活动,则最大和最小平均功耗会相差很大。

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