Power and Temperature Control on a 90-nm Itanium Family Processor

McGowen, R.; Poirier, C.; Bostak, C.; Ignowski, Jim; Millican, M.; Parks, W.H.; Naffziger, Samuel

doi:10.1109/jssc.2005.859902

Cited by 201 publications

(82 citation statements)

References 8 publications

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“…27 Performance wise, the dynamic power consumed by a processor is proportional to the generated heat. 28 Dynamic power is related to the clock frequency by Equation (3).…”

Section: Introductionmentioning

confidence: 99%

Enhanced cooling in mono-crystalline ultra-thin silicon by embedded micro-air channels

et al. 2015

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In today’s digital world, complementary metal oxide semiconductor (CMOS) technology enabled scaling of bulk mono-crystalline silicon (100) based electronics has resulted in their higher performance but with increased dynamic and off-state power consumption. Such trade-off has caused excessive heat generation which eventually drains the charge of battery in portable devices. The traditional solution utilizing off-chip fans and heat sinks used for heat management make the whole system bulky and less mobile. Here we show, an enhanced cooling phenomenon in ultra-thin (>10 μm) mono-crystalline (100) silicon (detached from bulk substrate) by utilizing deterministic pattern of porous network of vertical “through silicon” micro-air channels that offer remarkable heat and weight management for ultra-mobile electronics, in a cost effective way with 20× reduction in substrate weight and a 12% lower maximum temperature at sustained loads. We also show the effectiveness of this event in functional MOS field effect transistors (MOSFETs) with high-κ/metal gate stacks.

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“…27 Performance wise, the dynamic power consumed by a processor is proportional to the generated heat. 28 Dynamic power is related to the clock frequency by Equation (3).…”

Section: Introductionmentioning

confidence: 99%

Enhanced cooling in mono-crystalline ultra-thin silicon by embedded micro-air channels

et al. 2015

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“…There also exist studies on thermal control for real-time systems such as [25]- [27], whose main goal is to resolve the thermal issue by tuning system parameters such as clock frequency, voltage and bandwidth allocation.…”

Section: Related Workmentioning

confidence: 99%

When thermal control meets sensor noise: analysis of noise-induced temperature error

Kim

Park

Eun

et al. 2015

21st IEEE Real-Time and Embedded Technology and Applications Symposium

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Abstract-Thermal control is critical for real-time systems as overheated processors can result in serious performance degradation or even system breakdown due to hardware throttling. The major challenges in thermal control for real-time systems are (i) the need to enforce both real-time and thermal constraints; (ii) uncertain system dynamics; and (iii) thermal sensor noise. Previous studies have resolved the first two, but the practical issue of sensor noise has not been properly addressed yet. In this paper, we introduce a novel thermal control algorithm that can appropriately handle thermal sensor noise. Our key observation is that even a small zero-mean sensor noise can induce a significant steady-state error between the target and the actual temperature of a processor. This steady-state error is contrary to our intuition that zero-mean sensor noise induces zero-mean fluctuations. We show that an intuitive attempt to resolve this unusual situation is not effective at all. By a rigorous approach, we analyze the underlying mechanism and quantify the noised-induced error in a closed form in terms of noise statistics and system parameters. Based on our analysis, we propose a simple and effective solution for eliminating the error and maintaining the desired processor temperature. Through extensive simulations, we show the advantages of our proposed algorithm, referred to as Thermal Control under Utilization Bound with Virtual Saturation (TCUB-VS).

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“…Later, in the early 2000s, when temperature began to become an important design constraint, more temperature monitors were allocated on-chip and the first standard interfaces appeared. For example, Intel's 90nm Montecito [5] included four temperature sensors with four ADC point-to-point connected to a microcontroller that was compliant with the Advanced Configuration and Power Interface (ACPI). Sensor data was used to control thermal and power policies such as DVFS.…”

Section: Previous Workmentioning

confidence: 99%

On-chip Monitoring: A Light-Weight Interconnection Network Approach

Ituero

López‐Vallejo

Marcos

et al. 2011

2011 14th Euromicro Conference on Digital System Design

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Current nanometer technologies are subjected to several adverse effects that seriously impact the yield and performance of integrated circuits. Such is the case of within-die parameters uncertainties, varying workload conditions, aging, temperature, etc. Monitoring, calibration and dynamic adaptation have appeared as promising solutions to these issues and many kinds of monitors have been presented recently. In this scenario, where systems with hundreds of monitors of different types have been proposed, the need for light-weight monitoring networks has become essential. In this work we present a light-weight network architecture based on digitization resource sharing of nodes that require a time-todigital conversion. Our proposal employs a single wire interface, shared among all the nodes in the network, and quantizes the time domain to perform the access multiplexing and transmit the information. It supposes a 16% improvement in area and power consumption compared to traditional approaches.

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Power and Temperature Control on a 90-nm Itanium Family Processor

Cited by 201 publications

References 8 publications

Enhanced cooling in mono-crystalline ultra-thin silicon by embedded micro-air channels

Enhanced cooling in mono-crystalline ultra-thin silicon by embedded micro-air channels

When thermal control meets sensor noise: analysis of noise-induced temperature error

On-chip Monitoring: A Light-Weight Interconnection Network Approach

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