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Fundamental Thermal Limits on Data Retention in Low-Voltage CMOS Latches and SRAM

机译:低压CMOS闩锁和SRAM中数据保留的基本热限制

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Ultra-low-power systems with substantial computing capacity require latches and SRAMs to operate at extremely low supply voltages. However, with aggressive technology scaling, reliability becomes a major challenge due to unavoidable process variations and the presence of multiple noise sources, including intrinsic thermal noise. This paper provides a quantitative measure of reliability by calculating the probability distribution function (PDF) of errors induced by thermal noise in latches and SRAMs operating in subthreshold conditions. Implemented in a novel simulation tool for thermal-noise analysis of CMOS circuits (STTACC), our algorithm uses a stochastic differential equation circuit model that preserves the proper Poissonian statistics for thermal-noise-driven current fluctuations in MOSFETs. Our probabilistic error model can handle error rate analysis for arrays of latches or full SRAMs on time scales from seconds to years without excessive computational overhead. We demonstrate that the time-to-error (TTE) statistics of subthreshold SRAMs obey log-normal distributions that depend on parameters such as node and device capacitance, device threshold variations and operating conditions of supply voltage and temperature. This makes it possible to quantitatively evaluate the asymptotic behavior of extremely rare error events that are inaccessible to standard SPICE-based simulations.
机译:具有大量计算能力的超低功耗系统需要锁存器和SRAM以极低的电源电压运行。然而,由于攻击性技术缩放,由于不可避免的过程变化和多种噪声源的存在,可靠性成为主要挑战,包括多种噪声源,包括内在热噪声。本文通过计算锁扣条件中的锁存器中的热噪声引起的误差概率分布函数(PDF)提供了可靠性的定量测量。在CMOS电路(STTACC)的热噪声分析中实现的新型仿真工具中,我们的算法采用了一种随机微分方程电路模型,该电路模型可以保留用于MOSFET中的热噪声驱动电流波动的适当泊松统计。我们的概率误差模型可以处理锁存器或完整SRAM阵列的错误率分析,从秒到多年的时间范围内没有过度计算开销。我们证明亚阈值SRAMS的误差(TTE)统计遵循依赖于节点和设备电容的参数,设备阈值变化和供电电压和温度的操作条件的误差正常分布。这使得可以定量地评估标准香料的模拟无法访问的极少误差事件的渐近行为。

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