Temperature-Centric Reliability Analysis and Optimization of Electronic Systems Under Process Variation

Ukhov, Ivan; Eles, Petru; Peng, Zebo

doi:10.1109/tvlsi.2014.2371249

Cited by 11 publications

(3 citation statements)

References 18 publications

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“…The existing work in the context of uncertaintyaware design can be classified into three groups that, respectively, aim at (i) extracting uncertainty distributions of components as well as the correlation among them through observing variations in design parameters, 2,[4][5][6]12,14,17 (ii) deriving uncertainty at system level assuming that the uncertainty in analysis models or input parameters is estimated a priori, [18][19][20][21][22] and (iii) optimizing the system with respect to the estimated uncertainty in its design objectives. 23,24 To quantify uncertainty, Kaczer et al 6 investigate the effects of technology scaling on the variability of NBTI-based degradations in the threshold voltage.…”

Section: Related Workmentioning

confidence: 99%

Simulation-based uncertainty correlation modeling in reliability analysis

Khosravi

Müller

Glaß

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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Due to destructive effects like temperature and radiation, today's embedded systems have to deal with unreliable components. The intensity of these effects depends on uncertain aspects like environmental or usage conditions such that highly safety-critical systems are pessimistically designed for worst-case mission profiles. These uncertain aspects may affect several components simultaneously, implying correlation across uncertainties in their reliability. This paper enables a state-of-the-art uncertainty-aware reliability analysis technique to consider multiple arbitrary correlations; in other words, components' reliability is affected by several uncertain aspects to different degrees. This analysis technique combines reliability models such as binary decision diagrams with a Monte Carlo simulation, and derives the uncertainty distribution of the system's reliability with insights on the mean, quantile intervals, and so on. The proposed correlation method aims at generating correlated samples from the uncertainty distribution of components' reliability such that the shape and statistical properties of each individual distribution remain unchanged. Experimental results confirm that the proposed correlation model enables the employed uncertainty-aware analysis to accurately calculate uncertainty at system level.

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Section: Related Workmentioning

confidence: 99%

Simulation-based uncertainty correlation modeling in reliability analysis

Khosravi

Müller

Glaß

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…The approach to characterization of process variation developed in [116] is presented in Chapter 4. The techniques for analysis and design under process variation proposed in [111] and [112] are amalgamated in Chapter 5. The approach to analysis under workload variation introduced in [113] is elaborated on in Chapter 6.…”

Section: Publication Overviewmentioning

confidence: 99%

System-Level Analysis and Design under Uncertainty

Ukhov¹

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One major problem for the designer of electronic systems is the presence of uncertainty, which is due to phenomena such as process and workload variation. Very often, uncertainty is inherent and inevitable. If ignored, it can lead to degradation of the quality of service in the best case and to severe faults or burnt silicon in the worst case. Thus, it is crucial to analyze uncertainty and to mitigate its damaging consequences by designing electronic systems in such a way that uncertainty is effectively and efficiently taken into account.We begin by considering techniques for deterministic system-level analysis and design of certain aspects of electronic systems. These techniques do not take uncertainty into account, but they serve as a solid foundation for those that do. Our attention revolves primarily around power and temperature, as they are of central importance for attaining robustness and energy efficiency. We develop a novel approach to dynamic steady-state temperature analysis of electronic systems and apply it in the context of reliability optimization.We then proceed to develop techniques that address uncertainty. The first technique is designed to quantify the variability in process parameters, which is induced by process variation, across silicon wafers based on indirect and potentially incomplete and noisy measurements. The second technique is designed to study diverse system-level characteristics with respect to the variability originating from process variation. In particular, it allows for analyzing transient temperature profiles as well as dynamic steady-state temperature profiles of electronic systems. This is illustrated by considering a problem of design-space exploration with probabilistic constraints related to reliability. The third technique that we develop is designed to efficiently tackle the case of sources of uncertainty that are less regular than process variation, such as workload variation. This technique is exemplified by analyzing the effect that workload units with uncertain processing times have on the timing-, power-, and temperature-related characteristics of the system under consideration.We also address the issue of runtime management of electronic systems that are subject to uncertainty. In this context, we perform an early investigation into the utility of advanced prediction techniques for the purpose of finegrained long-range forecasting of resource usage in large computer systems.All the proposed techniques are assessed by extensive experimental evaluations, which demonstrate the superior performance of our approaches to analysis and design of electronic systems compared to existing techniques. The research presented in this thesis has been partially funded by the National Computer Science Graduate School (cugs) in Sweden.v Sammanfattning Ett stort problem för designern inom elektroniska system är förekomsten av osäkerhet, som beror på sådana fenomen som variationer relaterade till tillverkning och arbetsbelastning. Osäkerhet är i många fall naturlig och oundv...

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“…The thermal model, similar to that in [138,144,52], is built upon the duality between heat transfer and electrical phenomena as an RC-lumped circuit. Specifically, the RC-model consists of three vertical, conductive layers for the die, heat spreader, and heat sink, and a fourth vertical, convective layer for the sink-to-air interface.…”

Section: Thermal Modelmentioning

confidence: 99%

The Thermal-Constrained Real-Time Systems Design on Multi-Core Platforms -- An Analytical Approach

Sha¹

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Temperature-Centric Reliability Analysis and Optimization of Electronic Systems Under Process Variation

Cited by 11 publications

References 18 publications

Simulation-based uncertainty correlation modeling in reliability analysis

Simulation-based uncertainty correlation modeling in reliability analysis

System-Level Analysis and Design under Uncertainty

The Thermal-Constrained Real-Time Systems Design on Multi-Core Platforms -- An Analytical Approach

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