Hierarchical Statistical Leakage Analysis and Its Application

Yang Xu, J. Teich
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引用次数: 1

Abstract

In this article, we investigate a hierarchical statistical leakage analysis (HSLA) design flow where module-level statistical leakage models supplied by IP vendors are used to improve the efficiency and capacity of SoC statistical leakage power analysis. To solve the challenges of incorporating spatial correlations between IP modules at system level, we first propose a method to extract correlation-inclusive leakage models. Then a method to handle the spatial correlations at system level is proposed. Using this method, the runtime of system statistical leakage analysis (SLA) can be significantly improved without disclosing the netlists of the IP modules. Experimental results demonstrate that the proposed HSLA method is about 100 times faster than gate-level full-chip SLA methods while maintaining the accuracy. In addition, we also investigate one application of this HSLA method, a leakage-yield-driven floorplanning framework, to demonstrate the benefits of such an HSLA method in practice. Moreover, an optimized hierarchical leakage analysis method dedicated to the floorplanning framework is proposed. The effectiveness of the floorplanning framework and the optimized method are confirmed by extensive experimental results.
分层统计泄漏分析及其应用
在本文中,我们研究了一种分层统计泄漏分析(HSLA)设计流程,其中使用IP供应商提供的模块级统计泄漏模型来提高SoC统计泄漏功率分析的效率和容量。为了解决在系统级别整合IP模块之间的空间相关性的挑战,我们首先提出了一种提取包含相关性的泄漏模型的方法。在此基础上,提出了一种系统级空间相关性处理方法。该方法可以在不泄露IP模块网络列表的情况下,显著提高系统统计泄漏分析(SLA)的运行时间。实验结果表明,该方法在保持精度的前提下,速度是门级全芯片SLA方法的100倍左右。此外,我们还研究了这种HSLA方法的一种应用,即泄漏收益驱动的地板规划框架,以证明这种HSLA方法在实践中的好处。此外,提出了一种针对平面规划框架的优化分层渗漏分析方法。大量的实验结果证实了该平面规划框架和优化方法的有效性。
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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