计算机工程
計算機工程
계산궤공정
COMPUTER ENGINEERING
2015年
4期
41-47
,共7页
大数据%热感知%热可靠性%服务器%能源冷却成本%集群
大數據%熱感知%熱可靠性%服務器%能源冷卻成本%集群
대수거%열감지%열가고성%복무기%능원냉각성본%집군
big data%thermal-aware%thermal-reliability%server%energy cooling costs%clusters
大数据极速发展使超大型大数据分析平台不断涌现，导致能源成本急剧上升。为保证服务器的热可靠性，提出一种以数据处理为中心的能源冷却成本技术。该技术考虑了服务器不均衡热力特性、热力稳定性负载阈值差异以及集群大数据语义差异等，对文件进行主动式热感知布局，从而在不影响性能的前提下降低冷却能源成本，保证大数据分析集群的热可靠性。基于Yahoo公司一个月的真实大数据分析对该技术进行评估，实验结果表明，该技术可使冷却成本下降42%，总体性能是当前无关冷却技术的9倍。
大數據極速髮展使超大型大數據分析平檯不斷湧現，導緻能源成本急劇上升。為保證服務器的熱可靠性，提齣一種以數據處理為中心的能源冷卻成本技術。該技術攷慮瞭服務器不均衡熱力特性、熱力穩定性負載閾值差異以及集群大數據語義差異等，對文件進行主動式熱感知佈跼，從而在不影響性能的前提下降低冷卻能源成本，保證大數據分析集群的熱可靠性。基于Yahoo公司一箇月的真實大數據分析對該技術進行評估，實驗結果錶明，該技術可使冷卻成本下降42%，總體性能是噹前無關冷卻技術的9倍。
대수거겁속발전사초대형대수거분석평태불단용현，도치능원성본급극상승。위보증복무기적열가고성，제출일충이수거처리위중심적능원냉각성본기술。해기술고필료복무기불균형열력특성、열력은정성부재역치차이이급집군대수거어의차이등，대문건진행주동식열감지포국，종이재불영향성능적전제하강저냉각능원성본，보증대수거분석집군적열가고성。기우Yahoo공사일개월적진실대수거분석대해기술진행평고，실험결과표명，해기술가사냉각성본하강42%，총체성능시당전무관냉각기술적9배。
Explosion in big data has led to a surge in extremely large scale big data analytics platforms, resulting in burgeoning energy costs. In order to ensure the thermal-reliability of the servers, this paper proposes a data-centric technology for reducing cooling energy costs. It considers the uneven thermal-profile of the servers,the differences in their thermal-reliability-driven load thresholds,and differences in the data-semantics of the big data placed in the cluster. Based on this knowledge,the proposed technology does proactive,thermal-aware file placement,which ensures to reduce cooling energy costs and ensures thermal-reliability in the big data analytics cluster without any performance impact. Evaluation results with one-month long real-world big data analytics production traces from Yahoo Experimental results show that the technology reaches 42% reduction in the cooling energy costs and 9 x better performance than the state-of-the-art data-agnostic cooling techniques.
