Correlation of Prediction to On-Orbit SEU Performance for a Commercial 0.25-$\mu$m CMOS SRAM

Hansen, D. L.; Jobe, K.; Whittington, J.; Shoga, M.; Sunderland, D.A.

doi:10.1109/tns.2007.908787

Cited by 28 publications

(4 citation statements)

References 23 publications

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“…The concept of LET has been developed continually to meet the improving radiation effect research, for example, the effective LET as defined by the standard inverse cosine law was developed for the angled irradiation. [11][12][13]…”

Section: Experiments Resultsmentioning

confidence: 99%

Discussion of the metric in characterizing the single-event effect induced by heavy ions

Zhang¹,

Zhang²,

Luo³

et al. 2013

Chinese Phys. B

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The single-event effect (SEE) is the most serious problem in space environment. The modern semiconductor technology is concerned with the feasibility of the linear energy transfer (LET) as metric in characterizing SEE induced by heavy ions. In this paper, we calibrate the detailed static random access memory (SRAM) cell structure model of an advanced field programmable gate array (FPGA) device using the computer-aided design tool, and calculate the heavy ion energy loss in multi-layer metal utilizing Geant4. Based on the heavy ion accelerator experiment and numerical simulation, it is proved that the metric of LET at the device surface, ignoring the top metal material in the advanced semiconductor device, would underestimate the SEE. In the SEE evaluation in space radiation environment the top-layers on the semiconductor device must be taken into consideration.

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Section: Experiments Resultsmentioning

confidence: 99%

Discussion of the metric in characterizing the single-event effect induced by heavy ions

Zhang¹,

Zhang²,

Luo³

et al. 2013

Chinese Phys. B

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“…Thus, the SPEs could be strong enough to cause hazards in space applications. For example, the measured SEU rate of a 4k*32 bit 0.25 µm CMOS SRAM module in a geostationary satellite during a few SPEs is illustrated in Table I [21]. The approximate value of the background upset rate is obtained by linear fitting to the monthly average data.…”

Section: Space Radiationmentioning

confidence: 99%

“…The CREME96 suite uses the RPP model (Rectangular Parallelepiped Parallelogram) [36] for direct ionization induced upset events calculation, in which the bit SV is assumed to have this shape. Choosing the RPP thickness that conforms to the device cross-section direction dependence is not trivial [21]. For the sake of simplicity, the RPP value recommended by CREME96 was selected, in which lateral dimensions 𝑥 and 𝑦 are determined as the square root of the limiting cross-section for each bit, and the device depth 𝑧 is 0.5 𝑢𝑚.…”

Section: Seu Rate Estimationmentioning

confidence: 99%

Solar Particle Event and Single Event Upset Prediction from SRAM-based Monitor and Supervised Machine Learning

Chen

Lange

Andjelković

et al. 2022

IEEE Trans. Emerg. Topics Comput.

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The intensity of cosmic radiation may differ over five orders of magnitude within a few hours or days during the Solar Particle Events (SPEs), thus increasing for several orders of magnitude the probability of Single Event Upsets (SEUs) in spaceborne electronic systems. Therefore, it is vital to enable the early detection of the SEU rate changes in order to ensure timely activation of dynamic radiation hardening measures. In this paper, an embedded approach for the prediction of SPEs and SRAM SEU rate is presented. The proposed solution combines the real-time SRAM-based SEU monitor, the offline-trained machine learning model and online learning algorithm for the prediction. With respect to the state-of-the-art, our solution brings the following benefits: (1) Use of existing on-chip data storage SRAM as a particle detector, thus minimizing the hardware and power overhead, (2) Prediction of SRAM SEU rate one hour in advance, with the fine-grained hourly tracking of SEU variations during SPEs as well as under normal conditions, (3) Online optimization of the prediction model for enhancing the prediction accuracy during runtime, (4) Negligible cost of hardware accelerator design for the implementation of selected machine learning model and online learning algorithm. The proposed design is intended for a highly dependable and self-adaptive multiprocessing system employed in space applications, allowing to trigger the radiation mitigation mechanisms before the onset of high radiation levels.

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“…Comparison of OSOT simulation results with CREME96 and flight data adapted from Ref. [19] An example of simulation with the OSOT is shown in Fig.6.…”

Section: B Error Probability Response Functionmentioning

confidence: 99%

Methodology of soft error rate computation in modern microelectronics

Зебрев

Ishutin

Useinov

et al. 2009

2009 European Conference on Radiation and Its Effects on Components and Systems

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We have proposed a test methodology based on successive experimental determination of angular cross-section dependence followed be averaging over full solid angle. Equivalence between phenomenological and chord-length distribution averaging for soft error rate computation is shown. Role of energy-loss straggling in subthreshold error rate enhancement has been revealed. Nuclear reaction induced error rate computation method providing crossover between BGR and chord-length approaches has been proposed. Possibility of inclusion of multiple bit error rate estimation in a unified computational scheme is shown.

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Correlation of Prediction to On-Orbit SEU Performance for a Commercial 0.25-$\mu$m CMOS SRAM

Cited by 28 publications

References 23 publications

Discussion of the metric in characterizing the single-event effect induced by heavy ions

Discussion of the metric in characterizing the single-event effect induced by heavy ions

Solar Particle Event and Single Event Upset Prediction from SRAM-based Monitor and Supervised Machine Learning

Methodology of soft error rate computation in modern microelectronics

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