A Case Study of Energy Aware Scheduling on SuperMUC

In this paper, we analyze the functionalities for energy aware scheduling of the IBM LoadLeveler resource management system on SuperMUC, one of the world’s fastest HPC systems. We explain how LoadLeveler predicts execution times and the average power consumption of the system’s workloads at varying...

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Bibliographic Details
Published inSupercomputing pp. 394 - 409
Main Authors Auweter, Axel, Bode, Arndt, Brehm, Matthias, Brochard, Luigi, Hammer, Nicolay, Huber, Herbert, Panda, Raj, Thomas, Francois, Wilde, Torsten
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing 2014
SeriesLecture Notes in Computer Science
Subjects
energy aware scheduling
HPC
power modelling
resource management
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Summary:In this paper, we analyze the functionalities for energy aware scheduling of the IBM LoadLeveler resource management system on SuperMUC, one of the world’s fastest HPC systems. We explain how LoadLeveler predicts execution times and the average power consumption of the system’s workloads at varying CPU frequencies and compare the prediction to real measurements conducted on various benchmarks. Since the prediction model proves to be accurate for our application workloads, we can analyze the LoadLeveler predictions for a large fraction of the SuperMUC application portfolio. This enables us to define a policy for energy aware scheduling on SuperMUC, which selects the CPU frequencies considering the applications’ power and performance characteristics thereby providing an optimized tradeoff between energy savings and execution time.
ISBN:9783319075174
3319075179
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-07518-1_25