Abstract
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.
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Auweter, A. et al. (2014). A Case Study of Energy Aware Scheduling on SuperMUC. In: Kunkel, J.M., Ludwig, T., Meuer, H.W. (eds) Supercomputing. ISC 2014. Lecture Notes in Computer Science, vol 8488. Springer, Cham. https://doi.org/10.1007/978-3-319-07518-1_25
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DOI: https://doi.org/10.1007/978-3-319-07518-1_25
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07517-4
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