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    • 8. 发明授权
    • Defining statistical sensitivity for timing optimization of logic circuits with large-scale process and environmental variations
    • 定义具有大规模工艺和环境变化的逻辑电路的时序优化的统计灵敏度
    • US07487486B2
    • 2009-02-03
    • US11629445
    • 2005-06-11
    • Mustafa CelikJiayong LeLawrence PileggiXin Li
    • Mustafa CelikJiayong LeLawrence PileggiXin Li
    • G06F17/50G06F7/60G06F7/52
    • G06F17/5031G06F2217/10
    • The large-scale process and environmental variations for today's nano-scale ICs are requiring statistical approaches for timing analysis and optimization (1). Significant research has been recently focused on developing new statistical timing analysis algorithms (2), but often without consideration for how one should interpret the statistical timing results for optimization. The invention provides a sensitivity-based metric (2) to assess the criticality of each path and/or arc in the statistical timing graph (4). The statistical sensitivities for both paths and arcs are defined. It is shown that path sensitivity is equivalent to the probability that a path is critical, and arc sensitivity is equivalent to the probability that an arc sits on the critical path. An efficient algorithm with incremental analysis capability (2) is described for fast sensitivity computation that has a linear runtime complexity in circuit size. The efficacy of the proposed sensitivity analysis is demonstrated on both standard benchmark circuits and large industry examples.
    • 目前的纳米尺度IC的大规模工艺和环境变化需要用于时序分析和优化的统计方法(1)。 最近重点研究重点是开发新的统计时序分析算法(2),但往往不考虑如何解释统计时序结果进行优化。 本发明提供了一种基于灵敏度的度量(2)来评估统计时序图(4)中每个路径和/或弧的关键性。 定义了路径和弧线的统计灵敏度。 显示路径灵敏度等于路径关键的概率,弧敏感度等于弧位于关键路径上的概率。 描述了具有增量分析能力的有效算法(2),用于快速灵敏度计算,其电路尺寸具有线性运行时间复杂度。 提出的灵敏度分析的功效在标准基准电路和大型行业实例中得到证明。
    • 10. 发明申请
    • Defining Statistical Sensitivity for Timing Optimization of Logic Circuits with Large-Scale Process and Environmental Variations
    • 定义具有大规模过程和环境变化的逻辑电路的时序优化的统计灵敏度
    • US20080072198A1
    • 2008-03-20
    • US11629445
    • 2005-06-11
    • Mustafa CelikJiayong LeLawrence PileggiXin Li
    • Mustafa CelikJiayong LeLawrence PileggiXin Li
    • G06F17/50
    • G06F17/5031G06F2217/10
    • The large-scale process and environmental variations for today's nano-scale ICs are requiring statistical approaches for timing analysis and optimization (1). Significant research has been recently focused on developing new statistical timing analysis algorithms (2), but often without consideration for how one should interpret the statistical timing results for optimization. The invention provides a sensitivity-based metric (2) to assess the criticality of each path and/or arc in the statistical timing graph (4). The statistical sensitivities for both paths and arcs are defined. It is shown that path sensitivity is equivalent to the probability that a path is critical, and arc sensitivity is equivalent to the probability that an arc sits on the critical path. An efficient algorithm with incremental analysis capability (2) is described for fast sensitivity computation that has a linear runtime complexity in circuit size. The efficacy of the proposed sensitivity analysis is demonstrated on both standard benchmark circuits and large industry examples.
    • 目前的纳米尺度IC的大规模工艺和环境变化需要用于时序分析和优化的统计方法(1)。 最近重点研究重点是开发新的统计时序分析算法(2),但往往不考虑如何解释统计时序结果进行优化。 本发明提供了一种基于灵敏度的度量(2)来评估统计时序图(4)中每个路径和/或弧的关键性。 定义了路径和弧线的统计灵敏度。 显示路径灵敏度等于路径关键的概率,弧敏感度等于弧位于关键路径上的概率。 描述了具有增量分析能力的有效算法(2),用于快速灵敏度计算,其电路尺寸具有线性运行时间复杂度。 提出的灵敏度分析的功效在标准基准电路和大型行业实例中得到证明。