Variation-Aware System-Level Power Analysis

Chandra, Saumya; Lahiri, Kanishka; Raghunathan, Anand; Dey, Sujit

doi:10.1109/tvlsi.2009.2021478

Cited by 7 publications

(11 citation statements)

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“…Process variation has been the topic of many lines of research; see, for instance, [6,7,11,58,69,117]. Similarly, workload uncertainty has not been deprived of attention; see, for instance, [32,88,96,98,105,124].…”

Section: Previous Workmentioning

confidence: 99%

“…A solely power-targeted but temperature-aware solution is proposed in [11] where the working force of the analysis is mc sampling with partially precomputed data. A learning-based approach is presented in [59] in order to estimate the maximum temperature under the static steady-state condition; recall Section 3.3.…”

Section: Previous Workmentioning

confidence: 99%

“…To summarize, the prior techniques for probabilistic power and temperature analysis are restricted in use due to one or several of the following traits: (a) based on mc simulations (potentially slow) [11], (b) limited to power analysis [6,7,11,44,99,117], (c) ignoring the power-temperature interplay [6,7,44,51,99,117], (d) limited to the static steady-state temperature [51,58,59,69], (e) exclusive focus on the maximum temperature [59], and (f ) a priori chosen distributions of power and temperature [6,58,103]. The designer's toolbox does not yet include tools for transient analysis and dynamic steady-state analysis under process variation, which are of great importance for certain applications.…”

Section: Analysis and Design Under Process Uncertaintymentioning

confidence: 99%

“…Therefore, such variations are often conveniently modeled using Gaussian random variables [6,11,44,51,58,59,69,99,103]. Due to the underlying physics and for demonstration purposes, we take a step further and embed into the model the fact that the effective channel length-occupying the space between the drain and source of a transistor-cannot be arbitrarily large or take negative values, which Gaussian distributions allow it to do.…”

Section: Problem Formulationmentioning

confidence: 99%

“…It can be seen that the curves are nearly indistinguishable; however, the beta one has a bounded support [−4, 4], which can potentially lead to more realistic models. The variability in u is split into global and local parts [11,58,99], which are denoted by u glob and u loc , respectively. The former can be treated as a composition of inter-lot, inter-wafer, and inter-die variations, and the latter as a composition of intra-die variations.…”

Section: Problem Formulationmentioning

confidence: 99%

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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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Section: Previous Workmentioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

Section: Analysis and Design Under Process Uncertaintymentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

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System-Level Analysis and Design under Uncertainty

Ukhov¹

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Probabilistic Analysis of Power and Temperature Under Process Variation for Electronic System Design

Ukhov

Eles

Peng

2014

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Electronic system design based on deterministic techniques for power-temperature analysis is, in the context of current and future technologies, both unreliable and inefficient since the presence of uncertainty, in particular, due to process variation, is disregarded. In this paper, we propose a flexible probabilistic framework targeted at the quantification of the transient power and temperature variations of an electronic system. The framework is capable of modeling diverse probability laws of the underlying uncertain parameters and arbitrary dependencies of the system on such parameters. For the considered system, under a given workload, our technique delivers analytical representations of the corresponding stochastic power and temperature profiles. These representations allow for a computationally efficient estimation of the probability distributions and accompanying quantities of the power and temperature characteristics of the system. The approximation accuracy and computational time of our approach are assessed by a range of comparisons with Monte Carlo simulations, which confirm the efficiency of the proposed technique.Index Terms-Power analysis, process variation, system-level design, temperature analysis, uncertainty quantification.

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