Authors: Pierre-François Dutot; Yiannis Georgiou; David Glesser; Laurent Lefevre; Millian Poquet; Issam Rais

Energy consumption has become one of the mostcritical issues in the evolution of High Performance Computingsystems (HPC). Controlling the energy consumption of HPCplatforms is not only a way to control the cost but also a stepforward on the road towards exaflops. Powercapping is a widelystudied technique that guarantees that the platform will notexceed a certain power threshold instantaneously but it givesno flexibility to adapt job scheduling to a longer term energybudget control. We propose a job scheduling mechanism that extends thebackfilling algorithm to become energy-aware. Simultaneously, we adapt resource management with a node shutdown technique to minimize energy consumption whenever needed. Thiscombination enables an efficient energy consumption budgetcontrol on a cluster during a period of time. The technique isexperimented, validated and compared with various alternativesthrough extensive simulations. Experimentation results show highsystem utilization and limited bounded slowdown along withinteresting outcomes in energy efficiency while respecting anenergy budget during a particular time period.

Published in CCCGRID 2017.

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