scholarly journals Chip Temperature-Based Workload Allocation for Holistic Power Minimization in Air-Cooled Data Center

Energies ◽  
2017 ◽  
Vol 10 (12) ◽  
pp. 2123 ◽  
Author(s):  
Yan Bai ◽  
Lijun Gu
Keyword(s):  
Data Center ◽  
Power Minimization ◽  
Chip Temperature ◽  
Workload Allocation

Facility Cooling Failure Analysis of Direct Liquid Cooling System in Data Centers

2018 ◽  
Author(s):  
Sami Alkharabsheh ◽  
Udaya L. N. Puvvadi ◽  
Bharath Ramakrishnan ◽  
Kanad Ghose ◽  
Bahgat Sammakia
Keyword(s):  
Data Center ◽  
Cooling System ◽  
Rate Of Change ◽  
Operating Conditions ◽  
Thermal Mass ◽  
Liquid Cooling ◽  
Chip Temperature ◽  
Fan Speed ◽  
Liquid Cooling System ◽  
The Impact

This work experimentally studies the impact of facility cooling failure of a direct liquid cooling (DLC) system on the IT equipment (ITE). The facility side of a DLC system removes the heat from a secondary loop — in direct contact with the ITE — and discard it in a chiller loop or ambient. The CPU utilization and coolant set point temperature (SPT) are varied to understand the effect of failure under different operating conditions. The ITE response is studied in terms of chip temperature and power, and fan speed. It was found that failure of the facility cooling system is not hazardous to the IT operation. The rate of change in temperature after failure is low and is sufficient to turn the ITE off safely. This is attributed to the surrounding air in the data center and the thermal mass of the cooling system.

Power-aware workload allocation for green data centers

2018 ◽  
Vol 29 (4) ◽  
pp. 678-703
Author(s):  
Louma Ahmad Chaddad ◽  
Ali Chehab ◽  
Imad Elhajj ◽  
Ayman Kayssi
Keyword(s):  
Performance Optimization ◽  
Data Center ◽  
Data Centers ◽  
Energy Savings ◽  
Thermal State ◽  
Energy Performance ◽  
Content Type ◽  
Non Linear Programming ◽  
Server Selection ◽  
Workload Allocation

Purpose The purpose of this paper is to present an approach to reduce energy consumption in data centers. Subsequently, it reduces electricity bills and carbon dioxide footprints resulting from their use. Design/methodology/approach The authors present a mathematical model of the energy dissipation optimization problem. The authors formulate analytically the server selection problem and the supply air temperature as a non-linear programming, and propose an algorithm to solve it dynamically. Findings A simulation study on SimWare, using real workload traces, shows considerable savings for different data center sizes and utilization rates as compared to three other classic algorithms. The results prove that the proposed algorithm is efficient in handling the energy-performance trade-off, and that the proposed algorithm provides significant energy savings and maintains a relatively homogenous and stable thermal state at the different rack units in the data center. Originality/value The proposed algorithm ensures energy provisioning, performance optimization over existing state-of-the-art heuristics, and on-demand workload allocation.

scholarly journals A Dynamic Thermal-Allocation Solution to the Complex Economic Benefit for a Data Center

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Hui Liu ◽  
Wenyu Song ◽  
Tianqi Jin ◽  
Zhiyong Wu ◽  
Fusheng Yan ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Data Center ◽  
Economic Benefit ◽  
Data Centers ◽  
Economic Benefits ◽  
Dynamic Data ◽  
Workload Management ◽  
Profit Model ◽  
Thermal Distribution ◽  
Workload Allocation

Data centers, which provide computing services and gain profits, are indispensable to every city in the information era. They offer computation and storage while consuming energy and generate thermal discharges. To maximize the economic benefit, the existing research studies on the data center workload management mostly leverage the dynamical power model, i.e., the power-aware workload allocation. Nevertheless, we argue that for the complex relationship between the economic benefit and so many attributes, such as computation, energy consumption, thermal distribution, cooling, and equipment life, the thermal distribution dominates the others. Thus, thermal-aware workload allocation is more efficient. From the perspective of economic benefits, we propose a mathematical model for thermal distribution of a data center and study which workload distribution could determinately change the thermal distribution in the dynamic data center runtime, so as to reduce the cost and improve the economic benefits under the guarantee of service provisioning. By solving the thermal environment evaluation indexes, RHI (Return Heat Index) and RTI (Return Temperature Index), as well as heat dissipation models, we define quantitative models for the economic analysis such as energy consumption model for the busy servers and cooling, energy price model, and the profit model of data centers. Numerical simulation results validate our propositions and show that the average temperature of the data center reaches the best values, and the local hot spots are avoided effectively in various situations. As a conclusion, our studies contribute to the thermal management of the dynamic data center runtime for better economic benefits.

Power Minimization for Data Center with Guaranteed QoS

2015 ◽  
Author(s):  
Shuo Liu ◽  
Soamar Homsi ◽  
Ming Fan ◽  
Shaolei Ren ◽  
Gang Quan ◽  
...  
Keyword(s):  
Data Center ◽  
Power Minimization

Failure Analysis of Direct Liquid Cooling System in Data Centers

2017 ◽  
Author(s):  
Sami Alkharabsheh ◽  
Bharath Ramakrishnan ◽  
Bahgat Sammakia
Keyword(s):  
Data Center ◽  
Cooling System ◽  
System Failure ◽  
Liquid Cooling ◽  
Chip Temperature ◽  
Cpu Utilization ◽  
Speed Change ◽  
Main Factors ◽  
Liquid Cooling System ◽  
The Impact

In this paper, the impact of direct liquid cooling (DLC) system failure on the IT equipment is studied experimentally. The main factors that are anticipated to affect the IT equipment response during failure are the CPU utilization, coolant set point temperature (SPT) and the server type. These factors are varied experimentally and the IT equipment response is studied in terms of chip temperature and power, CPU utilization and total server power. It was found that failure of the cooling system is hazardous and can lead to data center shutdown in less than a minute. Additionally, the CPU frequency throttling mechanism was found to be vital to understand the change in chip temperature, power, and utilization. Other mechanisms associated with high temperatures were also observed such as the leakage power and the fans speed change. Finally, possible remedies are proposed to reduce the probability and the consequences of the cooling system failure.

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