电子学报Issue(10)：1904-1910,7.DOI:10.3969/j.issn.0372-2112.2015.10.004
GPU 集群能耗优化控制模型研究
Power Consu mption Optimization Control Model of GPU Clusters
摘要
Abstract
With the development of Big Data technology GPU cluster as a high efficiency parallel system applies into the Large-scale data computing field.Energy is a significant computation resource.So power consumption optimization control and cap-ping in real-time becomes a challenge issue.The Model Prediction Control strategy is introduced and a Multi-Input Multi-Output controller is built by using a closed loop feedback principle from the whole cluster perspective.Power consumption status is changed by scaling frequency and adjusting active stream multi-processors.Then the feedback and the periodic optimization mechanisms can predict the control behaviors in the future control cycles.This achieves the goal that reduces redundancy energy.The results demon-strate that the proposed model has more accuracy and comsumes less energy than the others.And it has better control stability.So it has better adaptability and obvious advantage in the Large-scale data real-time computing.关键词
能耗控制/GPU集群/能量消减/模型预测Key words
power consumption control/graphic processing unit (GPU)clusters/power capping/model prediction control分类
信息技术与安全科学引用本文复制引用
王海峰,曹云鹏..GPU 集群能耗优化控制模型研究[J].电子学报,2015,(10):1904-1910,7.基金项目
山东省自主创新及成果转化专项（No．2014ZZCX02702）；山东省自然科学基金（No．ZR2013FL005）；临沂大学博士科研启动项目 （）
