Accurate Temperature-Dependent Integrated Circuit Leakage Power Estimation is Easy

Liu, Yongpan; Dick, Robert P.; Shang, Li; Yang, Huazhong

doi:10.1109/date.2007.364517

Cited by 173 publications

(133 citation statements)

References 18 publications

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“…Power consumption, usually expressed as the sum of dynamic power and static power, influences system temperature, which in turn, exponentially affects static power [1]. This interdependency makes it unavoidable to consider temperature when dealing with power.…”

Section: A Power Consumption and Temperaturementioning

confidence: 99%

System-Level Modeling of Energy in TLM for Early Validation of Power and Thermal Management

Bouhadiba

Moy

Maraninchi

2013

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2013

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Abstract-Modern systems-on-a-chip are equipped with power architectures, allowing to control the consumption of individual components or subsystems. These mechanisms are controlled by a power-management policy often implemented in the embedded software, with hardware support. Today's circuits have an important static power consumption, whose low-power design require techniques like DVFS or power-gating. A correct and efficient management of these mechanisms is therefore becoming nontrivial. Validating the effect of the power management policy needs to be done very early in the design cycle, as part of the architecture exploration activity. High-level models of the hardware must be annotated with consumption information. Temperature must also be taken into account since leakage current increases exponentially with it.Existing annotation techniques applied to loosely-timed or temporally-decoupled models would create bad simulation artifacts on the temperature profile (e.g. unrealistic peaks). This paper addresses the instrumentation of a timed transactionlevel model of the hardware with information on the power consumption of the individual components. It can cope not only with power-state models, but also with Joule-per-bit traffic models, and avoids simulation artifacts when used in a functional/power/temperature co-simulation.

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Section: A Power Consumption and Temperaturementioning

confidence: 99%

System-Level Modeling of Energy in TLM for Early Validation of Power and Thermal Management

Bouhadiba

Moy

Maraninchi

2013

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2013

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“…Therefore, we detail only our empirical approach to extract the leakage current and switching capacitance. the temperature, q is the charge, V GS is the gate to source voltage, V th is the threshold voltage, n is the sub-threshold swing coefficient, and I gate is the gate leakage current [29,38]. These technology and parameters are then condensed into parameters denoted by c 1 and c 2 .…”

Section: Power Modelingmentioning

confidence: 99%

Predictive Dynamic Thermal and Power Management for Heterogeneous Mobile Platforms

Singla

Kaur

Unver

et al. 2015

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2015

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Heterogeneous multiprocessor systems-on-chip (MPSoCs) powering mobile platforms integrate multiple asymmetric CPU cores, a GPU, and many specialized processors. When the MPSoC operates close to its peak performance, power dissipation easily increases the temperature, hence adversely impacts reliability. Since using a fan is not a viable solution for hand-held devices, there is a strong need for dynamic thermal and power management (DTPM) algorithms that can regulate temperature with minimal performance impact. This abstract presents a DTPM algorithm based on a practical temperature prediction methodology using system identification. The DTPM algorithm dynamically computes a power budget using the predicted temperature, and controls the types and number of active processors as well as their frequencies. Experiments on an octa-core big.LITTLE processor and common Android apps demonstrate that the proposed technique predicts temperature within 3% accuracy, while the DTPM algorithm provides around 6× reduction in temperature variance, and as large as 16% reduction in total platform power compared to using a fan. Ogras, who not only taught and motivated me to pursue research, but also helped me achieve certain level of confidence and maturity. Without his valuable time, support and guidance, I could not have finished this work. I would also like to thank Dr. Bertan Bakkaloglu and Dr. Ali Unver for taking out time and agreeing to be a part of my thesis defense committee.

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“…A recent study shows that highly-efficient and accurate temperature-dependent leakage power analysis is possible using coarse-grained thermal modeling [11]. Leakage power mainly depends on IC thermal profile and circuit design style.…”

Section: Temperature-dependent Leakage Power Analysismentioning

confidence: 99%

Power, Thermal, and Reliability Modeling in Nanometer-Scale Microprocessors

et al. 2007

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Power is the source of the greatest problems facing microprocessor designers. High-power processors rapidly deplete battery energy. Rapid changes in power consumption result in on-chip voltage fluctuations that bring transient errors. High spatial and temporal power densities bring high temperatures, which result in decreased lifetime reliability. High temperatures also increase leakage power consumption, thereby closing a self-reinforcing powertemperature feedback loop. The effects of increasing power consumption, power variation, and power density are expensive and distasteful. The wages of power are bulky short-lived batteries, huge heatsinks, large on-die capacitors, high server electric bills, and unreliable microprocessors. The only alternative is optimizing microprocessor power consumption, temperature, and reliability. However, this depends on accurate modeling and rapid analysis of properties that span different disciplines and levels, from device physics, to numerical methods, to microarchitectural design. This article surveys the most important problems brought directly and indirectly by power consumption, indicates the relationships among them, explains recent methods of efficiently modeling them, and indicates promising directions in the ongoing fight against power.

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Accurate Temperature-Dependent Integrated Circuit Leakage Power Estimation is Easy

Cited by 173 publications

References 18 publications

System-Level Modeling of Energy in TLM for Early Validation of Power and Thermal Management

System-Level Modeling of Energy in TLM for Early Validation of Power and Thermal Management

Predictive Dynamic Thermal and Power Management for Heterogeneous Mobile Platforms

Power, Thermal, and Reliability Modeling in Nanometer-Scale Microprocessors

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