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Power estimation methods for sequential logic circuits

机译:时序逻辑电路的功率估算方法

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Recently developed methods for power estimation have primarilynfocused on combinational logic. We present a framework for the efficientnand accurate estimation of average power dissipation in sequentialncircuits. Switching activity is the primary cause of power dissipationnin CMOS circuits. Accurate switching activity estimation for sequentialncircuits is considerably more difficult than that for combinationalncircuits, because the probability of the circuit being in each of itsnpossible states has to be calculated. The Chapman-Kolmogorov equationsncan be used to compute the exact state probabilities in steady state.nHowever, this method requires the solution of a linear system ofnequations of size 2N where N is the number of flip-flops innthe machine. We describe a comprehensive framework for exact andnapproximate switching activity estimation in a sequential circuit. Thenbasic computation step is the solution of a nonlinear system ofnequations which is derived directly from a logic realization of thensequential machine. Increasing the number of variables or the number ofnequations in the system results in increased accuracy. For a widenvariety of examples, we show that the approximation scheme is withinn1-3% of the exact method, but is orders of magnitude faster for largencircuits. Previous sequential switching activity estimation methods cannhave significantly greater inaccuracies
机译:最近开发的功率估计方法主要集中在组合逻辑上。我们提出了一个高效,准确地估计时序电路平均功耗的框架。开关活动是CMOS电路功耗的主要原因。顺序电路的准确开关活动估计要比组合电路的准确得多,因为必须计算电路处于其每个不可能状态的概率。可以使用Chapman-Kolmogorov方程来计算稳态下的精确状态概率。但是,此方法需要求解大小为2N的线性系统,其中N是机器中触发器的数量。我们描述了用于在时序电路中精确和近似开关活动估计的综合框架。随后的基本计算步骤是直接从时序机器的逻辑实现中得出的非线性方程组的解决方案。增加系统中变量的数量或方程组的数量会导致精度提高。对于各种各样的例子,我们证明了近似方案在精确方法的1-3%之内,但是对于大型电路则要快几个数量级。先前的顺序转换活动估计方法无法显着提高误差

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