TY - GEN
T1 - Performance evaluation of energy-efficient high-speed tiered-storage system
AU - Akaike, Hirotoshi
AU - Fujimoto, Kazuhisa
AU - Miura, Kenji
AU - Muraoka, Hiroaki
PY - 2010
Y1 - 2010
N2 - Large-scale high-performance storage in high-performance computing systems consists of numerous HDDs and consumes a large amount of energy. To reduce the energy consumed by these storage systems, we previously proposed a high-speed tiered-storage system with a power-aware proactive method of storage-tiering management, which we named the energy-efficient high-speed tiered-storage system (eHiTS). eHiTS consists of a high-speed online storage component as the first tier and a large capacity nearline storage component as the second tier. The first-tier online storage is used as a data cache. For reducing energy consumption, it is necessary to reduce the online storage capacity, but this decreases performance. We derive the relationship between performance and online storage capacity by analytical calculation and simulation with an actual HPC system. The results show that with a 1% of decrease in performance, online capacity could be reduced to the capacity which can hold about 1.4 times as many volumes as the maximum number of volumes required by jobs running in parallel. In this case, energy consumption was reduced by an estimated 38% with eHiTS compared with conventional tiered-storage systems.
AB - Large-scale high-performance storage in high-performance computing systems consists of numerous HDDs and consumes a large amount of energy. To reduce the energy consumed by these storage systems, we previously proposed a high-speed tiered-storage system with a power-aware proactive method of storage-tiering management, which we named the energy-efficient high-speed tiered-storage system (eHiTS). eHiTS consists of a high-speed online storage component as the first tier and a large capacity nearline storage component as the second tier. The first-tier online storage is used as a data cache. For reducing energy consumption, it is necessary to reduce the online storage capacity, but this decreases performance. We derive the relationship between performance and online storage capacity by analytical calculation and simulation with an actual HPC system. The results show that with a 1% of decrease in performance, online capacity could be reduced to the capacity which can hold about 1.4 times as many volumes as the maximum number of volumes required by jobs running in parallel. In this case, energy consumption was reduced by an estimated 38% with eHiTS compared with conventional tiered-storage systems.
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U2 - 10.1109/INDIN.2010.5549661
DO - 10.1109/INDIN.2010.5549661
M3 - Conference contribution
AN - SCOPUS:77956583172
SN - 9781424473007
T3 - IEEE International Conference on Industrial Informatics (INDIN)
SP - 663
EP - 670
BT - Proceedings - INDIN 2010
T2 - 8th IEEE International Conference on Industrial Informatics, INDIN 2010
Y2 - 13 July 2010 through 16 July 2010
ER -
