{"title":"基于CPU利用率的最佳拟合能量预测模型","authors":"Xiao Zhang, Jian-Jun Lu, X. Qin","doi":"10.1109/NAS.2013.12","DOIUrl":null,"url":null,"abstract":"Energy cost becomes a major part of data center operational cost. Computer system consume more power when it runs under high workload. Many past studies focused on how to predict power consumption by performance counters. Some models retrieve performance counters from chips. Some models query performance counters from OS. Most of these researches were verified on several machines and claimed their models were accurate under the test. We found different servers have different energy consumption characters even with same CPU. In this paper, we present BFEPM, a best fit energy prediction model. It choose best model based on the power consumption benchmark result. We illustrate how to use benchmark result to find a best fit model. Then we validate the viability and effectiveness of model on all published results. At last, we apply the best fit model on two different machines to estimate the real-time energy consumption. The results show our model can get better results than single model.","PeriodicalId":213334,"journal":{"name":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"BFEPM: Best Fit Energy Prediction Modeling Based on CPU Utilization\",\"authors\":\"Xiao Zhang, Jian-Jun Lu, X. Qin\",\"doi\":\"10.1109/NAS.2013.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Energy cost becomes a major part of data center operational cost. Computer system consume more power when it runs under high workload. Many past studies focused on how to predict power consumption by performance counters. Some models retrieve performance counters from chips. Some models query performance counters from OS. Most of these researches were verified on several machines and claimed their models were accurate under the test. We found different servers have different energy consumption characters even with same CPU. In this paper, we present BFEPM, a best fit energy prediction model. It choose best model based on the power consumption benchmark result. We illustrate how to use benchmark result to find a best fit model. Then we validate the viability and effectiveness of model on all published results. At last, we apply the best fit model on two different machines to estimate the real-time energy consumption. The results show our model can get better results than single model.\",\"PeriodicalId\":213334,\"journal\":{\"name\":\"2013 IEEE Eighth International Conference on Networking, Architecture and Storage\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Eighth International Conference on Networking, Architecture and Storage\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAS.2013.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Eighth International Conference on Networking, Architecture and Storage","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAS.2013.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
BFEPM: Best Fit Energy Prediction Modeling Based on CPU Utilization
Energy cost becomes a major part of data center operational cost. Computer system consume more power when it runs under high workload. Many past studies focused on how to predict power consumption by performance counters. Some models retrieve performance counters from chips. Some models query performance counters from OS. Most of these researches were verified on several machines and claimed their models were accurate under the test. We found different servers have different energy consumption characters even with same CPU. In this paper, we present BFEPM, a best fit energy prediction model. It choose best model based on the power consumption benchmark result. We illustrate how to use benchmark result to find a best fit model. Then we validate the viability and effectiveness of model on all published results. At last, we apply the best fit model on two different machines to estimate the real-time energy consumption. The results show our model can get better results than single model.