{"title":"基于商品的高性能集群中权力意识的可行性分析","authors":"C. Hsu, Wu-chun Feng","doi":"10.1109/CLUSTR.2005.347063","DOIUrl":null,"url":null,"abstract":"We present a feasibility study of a power-reduction scheme that reduces the thermal power of processors by lowering frequency and voltage in the context of high-performance computing. The study revolves around a 16-processor Opteron-based Beowulf cluster, configured as four nodes of quad-processors, and shows that one can easily reduce a significant amount of CPU and system power dissipation and its associated energy costs while still maintaining high performance. Specifically, our study shows that a 5% performance slowdown can be traded off for an average of 19% system energy savings and 24% system power reduction. These preliminary empirical results, via real measurements, are encouraging because hardware failures often occur when the cluster is running hot, i.e, when the workload is heavy, and the new power-reduction scheme can effectively reduce a cluster's power demands during these busy periods","PeriodicalId":255312,"journal":{"name":"2005 IEEE International Conference on Cluster Computing","volume":"165 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"66","resultStr":"{\"title\":\"A Feasibility Analysis of Power Awareness in Commodity-Based High-Performance Clusters\",\"authors\":\"C. Hsu, Wu-chun Feng\",\"doi\":\"10.1109/CLUSTR.2005.347063\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a feasibility study of a power-reduction scheme that reduces the thermal power of processors by lowering frequency and voltage in the context of high-performance computing. The study revolves around a 16-processor Opteron-based Beowulf cluster, configured as four nodes of quad-processors, and shows that one can easily reduce a significant amount of CPU and system power dissipation and its associated energy costs while still maintaining high performance. Specifically, our study shows that a 5% performance slowdown can be traded off for an average of 19% system energy savings and 24% system power reduction. These preliminary empirical results, via real measurements, are encouraging because hardware failures often occur when the cluster is running hot, i.e, when the workload is heavy, and the new power-reduction scheme can effectively reduce a cluster's power demands during these busy periods\",\"PeriodicalId\":255312,\"journal\":{\"name\":\"2005 IEEE International Conference on Cluster Computing\",\"volume\":\"165 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"66\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 IEEE International Conference on Cluster Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CLUSTR.2005.347063\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE International Conference on Cluster Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLUSTR.2005.347063","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Feasibility Analysis of Power Awareness in Commodity-Based High-Performance Clusters
We present a feasibility study of a power-reduction scheme that reduces the thermal power of processors by lowering frequency and voltage in the context of high-performance computing. The study revolves around a 16-processor Opteron-based Beowulf cluster, configured as four nodes of quad-processors, and shows that one can easily reduce a significant amount of CPU and system power dissipation and its associated energy costs while still maintaining high performance. Specifically, our study shows that a 5% performance slowdown can be traded off for an average of 19% system energy savings and 24% system power reduction. These preliminary empirical results, via real measurements, are encouraging because hardware failures often occur when the cluster is running hot, i.e, when the workload is heavy, and the new power-reduction scheme can effectively reduce a cluster's power demands during these busy periods