Abstract
Exascale level of High Performance Computing (HPC) implies performance under stringent power constraints. Achieving power consumption targets for HPC systems requires hardware-software co-design to manage static and dynamic power consumption. We present extensions to the open source Global Extensible Open Power Manager (GEOPM) framework, which allows for rapid prototyping of various power and performance optimization strategies for exascale workloads. We have ported GEOPM to OpenPower\({^{\textregistered }}\) architecture and have used our modifications to investigate performance and power consumption optimization strategies for real-world scientific applications.
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Acknowledgements
Authors would like to acknowledge J. Eastep and C. Cantalupo, Intel, S. Bhat and T. Rosedahl, IBM Systems and D. Graham, STFC.
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Puzović, M., Elisseev, V., Jordan, K., Mcdonagh, J., Harrison, A., Sawko, R. (2018). Improving Performance and Energy Efficiency on OpenPower Systems Using Scalable Hardware-Software Co-design. In: Yokota, R., Weiland, M., Shalf, J., Alam, S. (eds) High Performance Computing. ISC High Performance 2018. Lecture Notes in Computer Science(), vol 11203. Springer, Cham. https://doi.org/10.1007/978-3-030-02465-9_28
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