{"title":"环面、K-Ary - n树和蜻蜓上的节能策略评价","authors":"F. Zahn, Armin Schoffer, H. Fröning","doi":"10.1109/HiPINEB.2018.00011","DOIUrl":null,"url":null,"abstract":"Energy is one of the most crucial factors in the design of large-scale computing systems, especially high-performance computing. While exascale systems could be built with current hardware solutions, the required funding exceeds the budget of most institutions. Since a system is never fully utilized, energy-proportional components can save a substantial amount of energy. However, current interconnect technologies still operate at a fixed power consumption rate. Therefore, network power consumption becomes increasingly important as its contribution to overall power consumption is increasing. Energy-proportional interconnection networks is a research area that is still emerging. In this work, we analyze the effects of different topology characteristics on power consumption and potential energy savings of interconnection networks. We compare the differences in the design of common topologies and the related impact to energy savings. In particular, we analyze the power consumption of torus, k-ary n-tree, and dragonfly. We also use existing topology-independent power-saving policies to derive potential energy savings for each topology and compare the policies to other work which is specific to topology hardware features. The comparison concludes that topology-independent policies are superior for energy savings and the other work is superior for execution time.","PeriodicalId":247186,"journal":{"name":"2018 IEEE 4th International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era (HiPINEB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Evaluating Energy-Saving Strategies on Torus, K-Ary N-Tree, and Dragonfly\",\"authors\":\"F. Zahn, Armin Schoffer, H. Fröning\",\"doi\":\"10.1109/HiPINEB.2018.00011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Energy is one of the most crucial factors in the design of large-scale computing systems, especially high-performance computing. While exascale systems could be built with current hardware solutions, the required funding exceeds the budget of most institutions. Since a system is never fully utilized, energy-proportional components can save a substantial amount of energy. However, current interconnect technologies still operate at a fixed power consumption rate. Therefore, network power consumption becomes increasingly important as its contribution to overall power consumption is increasing. Energy-proportional interconnection networks is a research area that is still emerging. In this work, we analyze the effects of different topology characteristics on power consumption and potential energy savings of interconnection networks. We compare the differences in the design of common topologies and the related impact to energy savings. In particular, we analyze the power consumption of torus, k-ary n-tree, and dragonfly. We also use existing topology-independent power-saving policies to derive potential energy savings for each topology and compare the policies to other work which is specific to topology hardware features. The comparison concludes that topology-independent policies are superior for energy savings and the other work is superior for execution time.\",\"PeriodicalId\":247186,\"journal\":{\"name\":\"2018 IEEE 4th International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era (HiPINEB)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 4th International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era (HiPINEB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HiPINEB.2018.00011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 4th International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era (HiPINEB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HiPINEB.2018.00011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluating Energy-Saving Strategies on Torus, K-Ary N-Tree, and Dragonfly
Energy is one of the most crucial factors in the design of large-scale computing systems, especially high-performance computing. While exascale systems could be built with current hardware solutions, the required funding exceeds the budget of most institutions. Since a system is never fully utilized, energy-proportional components can save a substantial amount of energy. However, current interconnect technologies still operate at a fixed power consumption rate. Therefore, network power consumption becomes increasingly important as its contribution to overall power consumption is increasing. Energy-proportional interconnection networks is a research area that is still emerging. In this work, we analyze the effects of different topology characteristics on power consumption and potential energy savings of interconnection networks. We compare the differences in the design of common topologies and the related impact to energy savings. In particular, we analyze the power consumption of torus, k-ary n-tree, and dragonfly. We also use existing topology-independent power-saving policies to derive potential energy savings for each topology and compare the policies to other work which is specific to topology hardware features. The comparison concludes that topology-independent policies are superior for energy savings and the other work is superior for execution time.