扩展前硅延迟模型后硅任务:验证,诊断,延迟测试,和速度分组

P. Das, S. Gupta
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引用次数: 10

摘要

所有后硅任务-验证,诊断,延迟测试和速度限制-必须通过将向量应用于实际芯片,并捕获和分析响应来执行。然而,必须使用电路的预硅模型来生成和分析所使用的矢量。三项全面的工业研究表明,现有的生成这些向量的方法是不充分的,一个主要的弱点是现有的延迟模型要么不能捕获过程变化,要么不能捕获显著影响延迟的高级延迟现象。因此,现有模型低估了导致选择非关键路径和生成不调用最坏情况延迟的向量的最坏情况延迟。在本文中,我们提出了一个简单的边界近似概念,并展示了它如何扩展任何现有的延迟模型,以捕获过程变化并消除任何低估。我们研究的主要问题是如何最好地使用这种方法来选择路径,并为后硅任务生成或评估向量。特别是,我们研究了使用这种方法绑定简单的pin-to-pin延迟模型或更高级的延迟模型是否更好。在时序分析层面,有界版本的引脚到引脚延迟模型具有较低的运行时复杂度,但边界较宽松。然而,我们进行了延迟测试的路径选择和延迟验证的向量生成,并表明更高级的延迟模型的有界版本在验证成本和运行时复杂性方面显着更有效。
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Extending pre-silicon delay models for post-silicon tasks: Validation, diagnosis, delay testing, and speed binning
All post-silicon tasks - validation, diagnosis, delay testing, and speed-binning - must be carried out by applying vectors to actual chips, and capturing and analyzing responses. Yet, vectors used must be generated and analyzed using pre-silicon models of the circuit. Three comprehensive industrial studies demonstrate that existing approaches for generating such vectors are inadequate, and one major weakness is that existing delay models either do not capture process variations or do not capture advanced delay phenomenon that significantly affect delays. Hence, existing models underestimate the worst case delay leading to selection of non-critical paths and generation of vectors that do not invoke worst case delays. In this paper, we propose a simple notion of bounding approximation and show how it can extend any existing delay model to also capture process variations and to eliminate any underestimation. The main question we investigate is how best to use this approach to select paths and generate or evaluate vectors for post silicon tasks. In particular, we study whether it is better to use this approach to bound simple pin-to-pin delay models or more advanced delay models. At the level of timing analysis, bounded versions of pin-to-pin delay models have lower run-time complexity but looser bounds. However, we conduct path selection for delay testing and vector generation for delay validation and show that bounded versions of more advanced delay models are significantly more efficient in terms of validation cost and runtime complexity.
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