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Towards Energy Budget Control in HPC

机译:在高性能计算中实现能源预算控制

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Energy consumption has become one of the most critical issues in the evolution of High Performance Computing systems (HPC). Controlling the energy consumption of HPC platforms is not only a way to control the cost but also a step forward on the road towards exaflops. Powercapping is a widely studied technique that guarantees that the platform will not exceed a certain power threshold instantaneously but it gives no flexibility to adapt job scheduling to a longer term energy budget control. We propose a job scheduling mechanism that extends the backfilling algorithm to become energy-aware. Simultaneously, we adapt resource management with a node shutdown technique to minimize energy consumption whenever needed. This combination enables an efficient energy consumption budget control on a cluster during a period of time. The technique is experimented, validated and compared with various alternatives through extensive simulations. Experimentation results show high system utilization and limited bounded slowdown along with interesting outcomes in energy efficiency while respecting an energy budget during a particular time period.
机译:能耗已成为高性能计算系统(HPC)演进中最关键的问题之一。控制HPC平台的能耗不仅是控制成本的一种方法,而且是向exaflops迈进的一步。 Powercapping是一项经过广泛研究的技术,可确保平台不会立即超过特定的功率阈值,但是它无法灵活地将作业调度适应长期的能源预算控制。我们提出了一种作业调度机制,该机制将回填算法扩展为能效感知。同时,我们采用节点关闭技术来调整资源管理,以在需要时将能耗降至最低。这种组合可以在一段时间内对群集进行有效的能耗预算控制。通过广泛的模拟,对该技术进行了实验,验证并与各种替代方法进行了比较。实验结果表明,在特定时间段内,在尊重能源预算的同时,系统利用率高,有限的有限减速以及有趣的能源效率结果。

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