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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qingwen Chen Grosso, P. van der Veldt, K. de Laat, C. Hofman, R. Bal, H. |
| Copyright Year | 2011 |
| Abstract | The Green Clouds project in the Netherlands investigates a system-level approach towards greening High-Performance Computing (HPC) infrastructures and clouds. In this paper we present our initial results in profiling virtual machines with respect to three power metrics, i.e. power, power efficiency and energy, under different high performance computing workloads. We built a linear power model that represents the behavior of a single work node and includes the contribution from individual components, i.e. CPU, memory and HDD, to the total power consumption of a single work node. Our results could be part of a power characterization module integrated into clusters' monitoring systems, future Green Clouds energy-savvy scheduler would use this monitoring system to support system-level optimization. |
| Starting Page | 768 |
| Ending Page | 775 |
| File Size | 1559711 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781467300063 |
| DOI | 10.1109/DASC.2011.131 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-12-12 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Measurement Energy consumption Power demand Green Clouds Stress Energy-efficient computing Power benchmark Cloud Computing Green products Memory management Kernel-based Virtual Machine (KVM) Benchmark testing Virtualization |
| Content Type | Text |
| Resource Type | Article |
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