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Robust metastability-based TRNG design in nanometer CMOS with sub-vdd pre-charge and hybrid self-calibration

机译:具有子VDD预充电和混合自校准的纳米CMOS中基于鲁棒的亚运动的TRNG设计

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In this work, we study the impact of sub-vdd pre-charge operation of metastability-based True Random Number Generator (TRNG) and propose a hybrid self-calibration to improve the statistics of the TRNG in the presence increasing intra-die variation. Circuits designed in deep submicron technologies are susceptible to process variation. The variability may affect the circuit performance, power and reliability. Numerous pre-silicon design methodologies and post-silicon circuit tuning mechanisms have been studied in literature. We propose a sub-vdd pre-charge technique to improve the tolerance of the TRNG to device mismatch. This is followed by a hybrid self-detection and calibration technique based on algorithmic post processing and circuit tuning to mitigate the effects of variability. The cryptographic metric of `bit entropy' is used to validate the proposed techniques. The TRNG circuit and the proposed techniques are implemented using 45nm PDK. Results show that variation in fabrication process affect the reliability of TRNG circuits. Pre-charging the TRNG to 0.7V for a typical supply voltage of 1.1V reduces the impact of device mismatch on the circuit by 2X for device mismatch as large as 4-5%. The hybrid self-calibration further improves the bit entropy by ~120% across a range of 5% intra-die variation. The simple control logic has an estimated area of 128 um2 and results in a negligible energy overhead of 0.82 fJ/bit.
机译:在这项工作中,我们研究了基于亚运动的真正随机数发生器(TRNG)的子VDD预充电操作的影响,并提出了混合自校准,以改善存在增加模具内变化的TRNG的统计数据。深度亚微米技术设计的电路易于处理变化。可变性可能会影响电路性能,功率和可靠性。在文献中研究了许多硅预硅设计方法和后硅电路调谐机构。我们提出了一个子VDD预充电技术,以提高TRNG到设备不匹配的容差。这是基于算法后处理和电路调谐的混合自测和校准技术,以减轻变异性的影响。 “位熵”的加密度量用于验证所提出的技术。使用45nm PDK实现TRNG电路和所提出的技术。结果表明,制造过程的变化影响了TRNG电路的可靠性。预先充电TRNG至0.7V为1.1V的典型电源电压降低了器件在电路上的影响2x,用于设备不匹配,大约4-5%。混合式自校准进一步改善了在5%的模具内变化范围内的比特熵〜120%。简单的控制逻辑具有128μm 2 的估计区域,并导致可忽略的能量开销为0.82 fj / bit。

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