Datacenter power savings through high ambient datacenter operation: CFD modeling study

Ahuja, Nishi

doi:10.1109/stherm.2012.6188833

Cited by 17 publications

(4 citation statements)

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“…Computational fluid dynamics (CFD) is popular tool for engineers. Workload placement techniques that rely upon CFD simulations [ 2 , 4 , 10 ] can give the estimation of thermal stress besides the data center power consumption for cooling and computing, if the location of servers, the inlet temperature variation, and thermal-stress phenomenon are included in the respective energy models. A technique to reduce recirculation of hot air inside data center [ 2 ] can perform better and save more cooling energy if the recirculation of hot air is distinguished from the natural heating-up of cold air after it is blown from vent tiles.…”

Section: Related Workmentioning

confidence: 99%

Minimizing Thermal Stress for Data Center Servers through Thermal-Aware Relocation

Chaudhry

Ling

Hussain

et al. 2014

The Scientific World Journal

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A rise in inlet air temperature may lower the rate of heat dissipation from air cooled computing servers. This introduces a thermal stress to these servers. As a result, the poorly cooled active servers will start conducting heat to the neighboring servers and giving rise to hotspot regions of thermal stress, inside the data center. As a result, the physical hardware of these servers may fail, thus causing performance loss, monetary loss, and higher energy consumption for cooling mechanism. In order to minimize these situations, this paper performs the profiling of inlet temperature sensitivity (ITS) and defines the optimum location for each server to minimize the chances of creating a thermal hotspot and thermal stress. Based upon novel ITS analysis, a thermal state monitoring and server relocation algorithm for data centers is being proposed. The contribution of this paper is bringing the peak outlet temperatures of the relocated servers closer to average outlet temperature by over 5 times, lowering the average peak outlet temperature by 3.5% and minimizing the thermal stress.

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Section: Related Workmentioning

confidence: 99%

Minimizing Thermal Stress for Data Center Servers through Thermal-Aware Relocation

Chaudhry

Ling

Hussain

et al. 2014

The Scientific World Journal

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“…Some studies found that 56% of the power consumption of the data center is consumed by the servers, 30% for cooling, 8% for power conditioning, and 5% by the networks [3]. Numerous studies have discussed how to improve data center power consumption by, e.g., improving server resource management [4], using new server hardware [5], and optimizing cooling [6,7]. In this paper we focus on the most power consuming element of data centers -the physical servers.…”

Section: Introductionmentioning

confidence: 99%

Power-performance tradeoffs in data center servers: DVFS, CPU pinning, horizontal, and vertical scaling

Krzywda

Ali-Eldin

Carlson

et al. 2018

Future Generation Computer Systems

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Dynamic Voltage and Frequency Scaling (DVFS), CPU pinning, horizontal, and vertical scaling, are four techniques that have been proposed as actuators to control the performance and energy consumption on data center servers. This work investigates the utility of these four actuators, and quantifies the power-performance tradeoffs associated with them. Using replicas of the German Wikipedia running on our local testbed, we perform a set of experiments to quantify the influence of DVFS, vertical and horizontal scaling, and CPU pinning on end-to-end response time (average and tail), throughput, and power consumption with different workloads. Results of the experiments show that DVFS rarely reduces the power consumption of underloaded servers by more than 5%, but it can be used to limit the maximal power consumption of a saturated server by up to 20% (at a cost of performance degradation). CPU pinning reduces the power consumption of underloaded server (by up to 7%) at the cost of performance degradation, which can be limited by choosing an appropriate CPU pinning scheme. Horizontal and vertical scaling improves both the average and tail response time, but the improvement is not proportional to the amount of resources added. The load balancing strategy has a big impact on the tail response time of horizontally scaled applications.

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“…In conjunction with an air or water-side economizer, an aisle containment architecture can realize significant savings in terms of the amount of energy used for cooling, especially when a data center is subject to high ambient temperatures [11,12]. Although the aisle containment architecture has been experimentally proven in terms of thermal management performance and cooling energy savings [13e18], little research has been conducted into the CFD modeling of the aisle containment architecture since it is difficult to consider air leakage without detailed measured data [19].…”

Section: Introductionmentioning

confidence: 99%

Impact of aisle containment on energy performance of a data center when using an integrated water-side economizer

Ham

Jeong

2016

Applied Thermal Engineering

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Datacenter power savings through high ambient datacenter operation: CFD modeling study

Cited by 17 publications

References 0 publications

Minimizing Thermal Stress for Data Center Servers through Thermal-Aware Relocation

Minimizing Thermal Stress for Data Center Servers through Thermal-Aware Relocation

Power-performance tradeoffs in data center servers: DVFS, CPU pinning, horizontal, and vertical scaling

Impact of aisle containment on energy performance of a data center when using an integrated water-side economizer

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