N. Ahuja, C. Rego, S. Ahuja, Matt Warner, Akhil Docca
{"title":"Data center efficiency with higher ambient temperatures and optimized cooling control","authors":"N. Ahuja, C. Rego, S. Ahuja, Matt Warner, Akhil Docca","doi":"10.1109/STHERM.2011.5767186","DOIUrl":null,"url":null,"abstract":"Advances in server technology have resulted in the cost of acquiring server equipment trending down, while economies of scale in data centers have significantly reduced the cost of labor. This leaves the cost of the energy as the next target for optimization. Energy costs are driven by operating the IT equipment, the switchgear that provides uninterrupted power to the equipment, and in cooling the IT equipment. In a typical datacenter, almost 40% of the total power consumption is spent on cooling. In addition, cooling effectiveness is a first order factor in determining the lifespan of the data center. One of the emerging trends in the industry is to move datacenter operations to higher ambient temperatures with some Operators wanting to set supply air temperatures as high as 40°C while improving cooling system efficiency. This study will show that with optimized cooling control one could reduce the total cost of ownership at the datacenter level by optimizing the datacenter cooling budget while ensuring no performance loss at increased ambient temperature conditions. This paper describes a platform-assisted thermal management approach that uses new sensors providing server airflow and server outlet temperature to improve control of the data centers cooling solution. This data is also used as input to a computational fluid dynamics (CFD) model for accurate predictive analysis and optimization of future change scenarios, thus increasing the data center efficiency and reducing power consumption. A key component of the study will be the use of computational fluid dynamics CFD analysis for optimizing the data center cooling system.","PeriodicalId":128077,"journal":{"name":"2011 27th Annual IEEE Semiconductor Thermal Measurement and Management Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 27th Annual IEEE Semiconductor Thermal Measurement and Management Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STHERM.2011.5767186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
Advances in server technology have resulted in the cost of acquiring server equipment trending down, while economies of scale in data centers have significantly reduced the cost of labor. This leaves the cost of the energy as the next target for optimization. Energy costs are driven by operating the IT equipment, the switchgear that provides uninterrupted power to the equipment, and in cooling the IT equipment. In a typical datacenter, almost 40% of the total power consumption is spent on cooling. In addition, cooling effectiveness is a first order factor in determining the lifespan of the data center. One of the emerging trends in the industry is to move datacenter operations to higher ambient temperatures with some Operators wanting to set supply air temperatures as high as 40°C while improving cooling system efficiency. This study will show that with optimized cooling control one could reduce the total cost of ownership at the datacenter level by optimizing the datacenter cooling budget while ensuring no performance loss at increased ambient temperature conditions. This paper describes a platform-assisted thermal management approach that uses new sensors providing server airflow and server outlet temperature to improve control of the data centers cooling solution. This data is also used as input to a computational fluid dynamics (CFD) model for accurate predictive analysis and optimization of future change scenarios, thus increasing the data center efficiency and reducing power consumption. A key component of the study will be the use of computational fluid dynamics CFD analysis for optimizing the data center cooling system.