Pre-CTS网表的瞬态时钟功率估计

Yonghwi Kwon, Jinwook Jung, Inhak Han, Youngsoo Shin
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引用次数: 9

摘要

时钟树合成(CTS)是在设计的最后阶段进行的。因此,在大多数设计阶段,只能在没有时钟网络的情况下进行功率估计,这是不可取的,因为时钟网络通常是最大的功耗消耗者。人们可以采用时钟功率的估计,但由于时钟门控所产生的动态性给预cts设计中的时钟功率估计带来了挑战。在本文中,我们(1)通过使用人工神经网络(ann)估计时钟树组件(时钟门控单元(CGC)和缓冲器以及它们的线负载);(2)使用它们时,每个CGC的门控或解门从一个网表中逐周期识别,以估计瞬态时钟功耗。少数测试电路的实验表明:(1)时钟树分量的估计误差平均为13%;(2)估计的时钟功率波形与实际波形非常接近,平均误差仅为2%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transient Clock Power Estimation of Pre-CTS Netlist
Clock tree synthesis (CTS) is performed in a very late stage of design. Power estimation, therefore, can only be done without clock network in most design stages, which is not desirable given that clock network is usually the biggest power consumer. One may adopt an estimate of clock power, but its dynamic nature arising from clock gating brings a challenge in the estimation of clock power in a pre-CTS design. In this paper, we (1) estimate the clock tree components (clock gating cells (CGCs) and buffers as well as their wireloads) by using artificial neural networks (ANNs) and (2) use them while gating or ungating of each CGC is identified from a netlist cycle-by-cycle to estimate transient clock power consumption. Experiments with a few test circuits indicate that (1) the estimation of clock tree components causes the error of 13% on average, and (2) the estimated clock power waveform is very close to the actual waveform with average error of only 2%.
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