Towards Generalizing 'Big Little' for Energy Proportional HPC and Cloud Infrastructures
| Autor: | Georges Da Costa, Laurent Lefèvre, Violaine Villebonnet, Jean-Marc Pierson, Patricia Stolf |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Consumption (economics)
020203 distributed computing business.industry Computer science Distributed computing Cloud computing 02 engineering and technology Energy consumption Virtualization computer.software_genre 7. Clean energy ARM architecture Embedded system Server 0202 electrical engineering electronic engineering information engineering Benchmark (computing) 020201 artificial intelligence & image processing Electricity business computer |
| Zdroj: | BDCloud |
| DOI: | 10.1109/bdcloud.2014.99 |
| Popis: | Reducing energy consumption is part of the main concerns in cloud and HPC environments. Today servers energy consumption is far from ideal, mostly because it remains very high even with low usage state. An energy consumption proportional to the server load would bring important savings in terms of electricity consumption and then financial costs for a data enter infrastructure. In this paper, we propose a platform composed of heterogeneous architectures to achieve proportional computing goal. We select low power ARM processor for a light load, and a range of regular x86 servers when performance is required. We propose a comparative study of benchmark execution in order to find the best configuration depending on the current load and show the effective results in terms of energy proportionality. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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