Novel IR/EM-Aware Power Grid Design and Analysis Methodologies for Optimal PPA at Sub-10nm Technology Nodes

Grant Miller, S. Jain, Santosh Kelgeri, Pranav Ranganathan, A. Ceyhan
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Abstract

In this paper, we introduce novel, holistic, electromigration-(EM) and dynamic voltage drop-aware power grid (PG) design and analysis methods that can help resolve the critical limitations that guard-band-driven approaches of today’s modern design closure flows enforce upon physical designers in their quest to achieve the best possible power/performance/area (PPA). These methods can easily be integrated into any existing design flow. The proposed structured strategies to co-optimize inherent trade-offs in PG reliability and PPA improvement can help enable higher transistor density and accurately quantify the impact of IR drop for block-level timing within conventional automatic place-and-route (PnR) flows through the use of an exhaustive, but low-cost in-house solution. We demonstrate up to 9% area savings and up to 5% power reduction while maintaining achievable frequency. The proposed flow updates pave the path for future work to apply our machine-learning-enhanced design space exploration approaches to better control trade-offs between PG reliability and PPA improvement.
新型红外/电磁敏感电网设计与分析方法在亚10nm技术节点的最优PPA
在本文中,我们介绍了新颖的、整体的、电迁移(EM)和动态电压降感知电网(PG)设计和分析方法,这些方法可以帮助解决当今现代设计封闭流的保护带驱动方法对物理设计师在追求最佳功率/性能/面积(PPA)时施加的关键限制。这些方法可以很容易地集成到任何现有的设计流程中。所提出的结构化策略可以共同优化PG可靠性和PPA改进的固有权衡,有助于实现更高的晶体管密度,并通过使用详尽但低成本的内部解决方案,准确量化传统自动放置和路由(PnR)流中IR下降对块级时序的影响。在保持可实现的频率的同时,我们展示了高达9%的面积节省和高达5%的功耗降低。提议的流程更新为未来的工作铺平了道路,应用我们的机器学习增强设计空间探索方法来更好地控制PG可靠性和PPA改进之间的权衡。
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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