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首页> 外文会议>13th International Workshop on Integrated Circuit and System Design: Power and Timing Modeling, Optimization and Simulation PATMOS 2003; Sep 10-12, 2003; Turin, Italy >Advanced Cell Modeling Techniques Based on Polynomial Expressions
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Advanced Cell Modeling Techniques Based on Polynomial Expressions

机译：基于多项式表达式的高级单元建模技术

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摘要

This paper presents an advance cell modeling technique based on polynomial expressions for physical and logic design. Till now, there lacks a modeling method to handle multiple operating points such as input slew, output capacitance, voltage, process, temperature, etc. at a time for the logic synthesis and physical design. Our novel curve-fitting algorithm for cell modeling can process a table with thousands of data points in a modeling equation compared to piecewise equations used in the existing methods. The number of data storage and CPU run time are significantly reduced without compromising the accuracy of the data. This ensures that the novel curve-fitting algorithm can exactly recover the original data points in a short period of time. In addition, the table-partitioning algorithm is developed to reduce the number of storage and flatten the peak situation occurring at some of the unsampled data. Furthermore, in order to filter the "pass" points with 99% of all data points, the algorithm is developed to select the best order for input variables, further causes to shorten CPU run time again. Our benchmark shows that the new approach has significantly better accuracy and less storage for both the sampling data and unsampling data.
机译：本文提出了一种基于多项式表达式的先进单元建模技术，用于物理和逻辑设计。到目前为止，还缺乏一种建模方法来同时处理多个工作点，例如输入摆率，输出电容，电压，工艺，温度等，以进行逻辑综合和物理设计。与现有方法中使用的分段方程相比，我们用于单元建模的新颖曲线拟合算法可以处理具有成千上万个数据点的表，该方程包含建模方程。数据存储量和CPU运行时间显着减少，而不会影响数据的准确性。这确保了新颖的曲线拟合算法可以在短时间内准确恢复原始数据点。此外，还开发了表分区算法，以减少存储数量并弄平某些未采样数据中出现的峰值情况。此外，为了用所有数据点的99％过滤“通过”点，开发了该算法以选择输入变量的最佳顺序，进一步导致再次缩短CPU运行时间。我们的基准测试表明，这种新方法在采样数据和非采样数据方面都具有明显更高的准确性和更少的存储空间。

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