Measurement of inherent noise in EDA tools

Measurement of inherent noise in EDA tools
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EDA 工具中固有噪声的测量

DOI:
10.1109/isqed.2002.996731
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发表时间:
2002
期刊:
Proceedings International Symposium on Quality Electronic Design
影响因子:
--
通讯作者:
S. Mantik
S. Mantik
中科院分区:
--
文献类型:
--
作者:
A. Kahng;S. Mantik

文献摘要

被引文献

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随着半导体技术的进步和设计复杂性的指数增长,设计工具的可预测性成为稳定的自顶向下设计过程的重要组成部分。单个工具解决方案质量的预测使设计人员能够使用工具在规定的资源范围内实现最佳解决方案,从而缩短设计周期。然而,随着EDA工具变得越来越复杂,它们变得越来越不可预测。可预测性损失的一个因素是两种算法中的固有噪声以及如何调用算法。在这项工作中,我们试图识别噪声源的EDA工具,并分析这些噪声源对设计质量的影响。我们的具体贡献是:(i)我们提出了新的行为标准的工具,相对于噪声的存在和管理;(ii)我们编译和分类的工具使用模型或工具架构,可以是噪声源的可能扰动;和(iii)我们评估的行为的工业场所和路线的工具相对于这些标准和噪声源。虽然行为准则为工具的稳定性提供了一些指导和特征,但我们并不建议工具免受输入扰动的影响。相反,噪声的分类使我们能够更好地理解工具将如何或应该如何表现;这最终可能使考虑固有工具噪声的改进工具预测器成为可能。
With advancing semiconductor technology and exponentially growing design complexities, predictability of design tools becomes an important part of a stable top-down design process. Prediction of individual tool solution quality enables designers to use tools to achieve best solutions within prescribed resources, thus reducing design cycle time. However, as EDA tools become more complex, they become less predictable. One factor in the loss of predictability is inherent noise in both algorithms and how the algorithms are invoked. In this work, we seek to identify sources of noise in EDA tools, and analyze the effects of these noise sources on design quality. Our specific contributions are: (i) we propose new behavior criteria for tools with respect to the existence and management of noise; (ii) we compile and categorize possible perturbations in the tool use model or tool architecture that can be sources of noise; and (iii) we assess the behavior of industry place and route tools with respect to these criteria and noise sources. While the behavior criteria give some guidelines for and characterize the stability of tools, we are not recommending that tools be immune from input perturbations. Rather, the categorization of noise allows us to better understand how tools will or should behave; this may eventually enable improved tool predictors that consider inherent tool noise.