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Circuit-Level NBTI Macro-Models for Collaborative Reliability Monitoring

机译:用于协作可靠性监控的电路级NBTI宏模型

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The increasing significance of Negative Bias Temperature Instability (NBTI) induced device-reliability degradation presents a compelling reason to perform efficient circuit-level reliability tracking. We propose a novel collaborative monitoring frame-work to track circuit level performance degradation caused specifically by NBTI. We use heterogeneous on-chip sensors to measure environmental and stress parameters and a macro-model to map the device-level degradation information into circuit-level reliability estimates. The macro-model is built using curve-fitted data and provides a practical upper bound of the path-delay-degradation to expect under a given set of dynamic parameters which includes operating conditions, process and stress parameters. Through usage of on-chip sensing resources we minimize the need for extensive circuit-specific analyses and also, the pessimism caused by assuming worst-case operating corners. We validate our approach on ISCAS-85 benchmarks and observe excellent correlation (>0.99) between worst-case SPICE observed and model-predicted path-delay degradation.
机译:负偏置温度不稳定(NBTI)诱导的装置可靠性降解的越来越重要提出了一种执行有效电路级可靠性跟踪的令人信服的原因。我们提出了一种新颖的协作监测框架,以跟踪NBTI专门引起的电路水平性能劣化。我们使用异构片上传感器来测量环境和应力参数和宏模型,以将设备级劣化信息映射到电路级可靠性估计。宏模型是使用曲线拟合数据构建的,并提供路径延迟劣化的实际上限,以期望在给定的一组动态参数下,包括操作条件,过程和应力参数。通过使用片上感测资源,我们最大限度地减少了对广泛的电路特异性分析的需求,并且还通过假设最坏情况的运行角来引起的悲观。我们在ISCAS-85基准上验证了我们的方法,并在最坏情况观察到和模型预测的路径延迟劣化之间观察出优异的相关性(> 0.99)。

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