Node sampling technique to speed up probability-based power estimation methods

Hoon Choi, Hansoo Kim, I. Park, S. Hwang, C. Kyung
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Abstract

We propose a new technique called node sampling to speed up the probability-based power estimation methods. It samples and processes only a small portion of total nodes to estimate the power consumption of a circuit. It is different from the previous speed-up techniques for probability-based methods in that the previous techniques reduce the processing time for each node while our method reduces the number of nodes actually processed. In addition, it is also different from the previous statistical sampling simulation techniques for simulation-based methods in that the previous methods sample the input vectors while our method samples the nodes in the network. The experimental results are very encouraging. The proposed method shows on the average more than 80% and 60% reductions of simulation run time under 20% and 5% error bounds, respectively.
节点采样技术加速了基于概率的功率估计方法
为了提高基于概率的功率估计方法的速度,我们提出了一种新的节点采样技术。它只对总节点的一小部分进行采样和处理,以估计电路的功耗。它与之前基于概率方法的加速技术的不同之处在于,之前的技术减少了每个节点的处理时间,而我们的方法减少了实际处理的节点数量。此外,与以往基于仿真方法的统计抽样仿真技术不同的是,以往的方法是对输入向量进行采样,而我们的方法是对网络中的节点进行采样。实验结果令人鼓舞。在20%和5%的误差范围内,所提出的方法分别平均减少了80%和60%的仿真运行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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